The use of Antibiotics and Implications for Antimicrobial ... · The second pathway is that of acquired resistance. Microorganisms can acquire antibiotic resistance by means of chance

The use of Antibiotics and Implications for

Antimicrobial Resistance

Development

Harald-Jan van Loon

Cover: Shaded Blue; are we at the end of the antibiotic era ?

Printed by Ponsen & Looijen bv grafisch bedrijf, Wageningen

ISBN 90-6464-935-9

Copyright © 2004 by H.J. van Loon

The use of Antibiotics and Implications for

Antimicrobial Resistance Development.

Het gebruik van antibiotica en implicaties voor

antimicrobiële resistentie. (met een Nederlandse samenvatting)

Proefschrift ter verkrijging van de graad van Doctor aan de Universiteit Utrecht

op gezag van de Rector Magnificus, Prof. Dr W.H. Gispen,

in gevolge het besluit van het College voor

promoties in het openbaar te verdedigen

op vrijdag 03 december 2004

des morgens om 10.30 uur

door

Harald-Jan van Loon

geboren op 15 februari 1974 te Brummen

Promotores: Prof. Dr Chr. van der Werken

Prof. Dr J. Verhoef

Co-promotor: Dr A.C. Fluit

Financial support for publication of this thesis was provided by:

Aventis Pharma, Ortomed BV, Stichting Bevordering

Wetenschappelijk Onderzoek in de Microbiologie and Chirurgisch

Fonds Universitair Medisch Centrum Utrecht.

For family, friends and colleagues

Contents

Chapter I Introduction 9

Chapter II Short versus Prolonged Antimicrobial Treatment During Open Management of the Abdomen.

27

Chapter III Predicting for Recurrence of Abdominal Sepsis and Mortality in Patients Undergoing Open Management of the Abdomen.

47

Chapter IV Antibiotic Rotation and Development of Gram-negative Antibiotic Resistance in ICU.

67

Chapter V Cross-Transmission of Microorganisms in a Surgical Intensive Care Unit.

97

Chapter VI A Highly Epidemic Enterobacter cloacae Clone.

113

Chapter VII The Evolution of Pseudomonas aeruginosa During Antibiotic Rotation in a Medical Intensive Care Unit.

129

Chapter VIII Evaluation of Genetic Determinants Involved in β-lactam- and Multi-Resistance in a Surgical ICU.

151

Chapter IX General Discussion and Summary 167

Chapter X Summary in Dutch 179

Aknowledgements 187

Curriculum vitae auctoris 191

Chapter I

Introduction

Chapter I

10

Introduction

Introduction Antibiotic resistance has reached pandemic proportions and the increasing incidences have alarmed medical healthcare associations world-wide.1 Some thirty years ago it was thought we had conquered almost all infectious diseases, but over the last decades we have witnessed the emergence of unknown infections and the re-emergence of known contagious diseases.2 This is partly due to a major increase in multi-resistant microorganisms, which have made infectious diseases more difficult to treat and have taken infectious diseases back into the focus of medical attention. Nowadays, in surgery and in intensive care units (ICU), patients can be treated with the most advanced technical equipment. However, surgical site infections (SSI) continue to be a major source of morbidity and mortality following operative procedures. In the United States SSIs are the second most common nosocomial infection, with approximately 500,000 SSIs occurring annually.3 In about 46% of these SSIs, gram-positive organisms are cultured of which many are resistant to virtually all antimicrobials leading to considerable morbidity and mortality and an exorbitant increase in infectious disease related health care costs.4,5 Epidemiology From the time penicillin was first discovered by Flemming in 1928 and during its widespread clinical use in the 1940’s dramatic changes in healthcare were observed with a sharp decrease of infectious disease related mortality, because patients who formerly died from infections could now be treated.6,7 However, soon penicillin became less effective and in the 1950’s widespread antimicrobial resistance to penicillin was observed. Fortunately this led to the introduction of newer, more potent and (semi-) synthetic antibiotics and the antimicrobial resistance problem was halted. However, this was only temporary, because soon increased resistance to the newer antibiotics was reported, which has ultimately led to the world-wide evolution of

11

Chapter I

a large diversity of antibiotic-resistant bacteria, of which some are even multi-drug resistant.8

The problem of antimicrobial resistance is known in hospitals world-wide. Often ICUs are regarded as the epicenters of antibiotic resistance and the source of outbreaks of multi-resistant bacteria. Obvious reasons for this are: the presence of critically ill patients on mechanical ventilation, with vascular and urinary catheters, giving the patients a higher risk for nosocomial infections and the widespread use of broad-spectrum antibiotics exerting selective pressure on bacteria.9-11 In addition, lack of enough nursing staff on the ward and crowding of patients may lead to a breakdown of infection control measures, which in its turn can lead to an increase of cross-contamination related resistance.12,13 Currently up to 20% of the patients admitted to ICUs in Europe develop a hospital-acquired infection.14 Ventilator associated pneumonia (VAP), bacteremia and urinary tract infections (UTI) are the most frequent hospital-acquired infections in ICU patients and are associated with considerable mortality.15 The type and frequency of infection evolve over time and vary from country to country.16 This was already made clear in 1992 in the European Prevalence of Infection (EPIC) study, which demonstrated marked differences in ICU-acquired infection rates and mortality of up to 30% in southern European countries, while only 10% in Scandinavia and Switzerland.17 The increase in antimicrobial resistance shows a similar distribution in Europe with the highest incidences in Mediterranean countries and the lowest in Scandinavia, Switzerland and The Netherlands.18 Concern is now focused on the Methicillin-Resistant Staphylococcus aureus (MRSA), the Vancomycin-Resistant Enterococci (VRE), the Extended-Spectrum Beta-Lactamases (ESBL), the fluoroquinolone-resistant Pseudomononas aeruginosa and the fluconazole-resistant Candida spp. These resistant pathogens have become the leading causes of hospital-acquired infections, especially in ICUs.19 In the past physicians have always relied on the development of new antimicrobial agents to deal with the evolving resistant microorganisms. However, with only a few new antibiotics in the pipe

12

Introduction

line of the pharmaceutical industry we are at severe risk of entering a post-antibiotic era with multi-drug resistant microorganisms.20,21 This means that we must be prudent in the use of the remaining effective antimicrobial agents that are currently at our disposal. Acquisition of antimicrobial resistance The presence and development of antibiotic resistance in bacteria can be related to two different pathways: The first is innate resistance, which is inherently present, meaning that microorganisms have a natural resistance to certain antibiotics, even if they were never confronted with these drugs. For example P. aeruginosa exhibit very low susceptibility to hydrophobic antibiotics such as macrolides, because these antibiotics have difficulty penetrating the outer membrane of P. aeruginosa. The second pathway is that of acquired resistance. Microorganisms can acquire antibiotic resistance by means of chance mutations (approximately 1 in 109), or through acquisition of DNA from another bacterium (horizontal gene transfer).22,23 Horizontal gene transfer is widely recognized as the mechanism responsible for the widespread distribution of antibiotic resistance genes. Horizontal gene transfer is mediated by conjugation, transduction or transformation. Conjugation is gene transfer by means of mobile genetic elements, called plasmids, which are extra-chromosomal DNA molecules that are transferred from the donor to another recipient bacterium through a so-called ‘sexual process’ (Fig. 1). The donor bacterium extrudes a specialized type of fimbria, the pilus, which makes direct contact with the donor and forms as a tube through which the extra-chromosomal DNA molecules are transferred. Besides plasmids, there are also mobile genetic elements called transposons, which are also capable of mediating the transfer of DNA by site-specific insertions and excisions. In addition, integrons carrying DNA target sequences can integrate resistant gene cassettes with corresponding target sequence. Transposons and integrons are frequently carried on plasmids, but can also have a chromosomal location.24

13

Chapter I

Figure 1: Transfer mechanisms of horizontal acquisition of resistance determinants. (A) Conjugation, (B) Transduction, (C) Transformation. (Sherris JC,ed., Medical Microbiology, Elsevier Science Publishing,1984)

Transduction is mediated by bacteriophages, which are viruses that attack bacteria. These bacteriophages can either replicate themselves and kill the bacterium, the lytic infection, or they can integrate their DNA into the bacterial chromosome, the lysogenic infection. After a bacteriophage has infected a bacterium it can cause a lytic infection and cut the bacterial DNA into pieces, which in turn can be packaged in new phage particles. These new phages can in turn infect other bacteria and the incoming segment of DNA can either be incorporated into the chromosome in the case of a lysogenic infection, or can be lost when there is another lytic infection. Transformation of resistance genes is the process of uptake of free DNA from the environment, e.g. after lysis of another bacterium. Specific structures or entry sites are required to allow the entry of this free DNA. After entry the exogenous DNA is recombined into the chromosome of the recipient bacterium.

14

Introduction

Antimicrobial resistance mechanisms The mechanisms exerting antimicrobial resistance can be divided into six main groups depending on the mechanisms involved:25 (a) The presence of an enzyme that directly inactivates the antibiotic,

e.g. beta-lactamase enzymes with beta-lactam antibiotics and phosphotransferases with aminoglycosides.

(b) The presence of an alternative enzyme in-stead of the one that is inhibited by the antibiotic, e.g. in tetracyline resistance the production of a protein that interacts with the ribosome, which is necessary for protein synthesis in the cytoplasm of a bacterium, renders the ribosome unaffected in the presence of the antibiotic. Reduced uptake of the antibiotic into the bacterial cytoplasm e.g. formation of altered penicillin-binding proteins (PBPs) in methicillin-resistant Staphylococcus aureus (MRSA), which show low affinity to the family of beta-lactam antibiotics, ensuring continued cell wall synthesis.

(c) Mutations of the target of the antibiotic, resulting in a reduced affinity of the antibiotic for its target site, e.g. a gyrA mutation in fluoroquinolone-resistant organisms, rendering the supercoiling process of the bacterial DNA unaffected by the antibiotic.

(d) Modifications of the target of the antibiotic, resulting in a reduced affinity of the antibiotic for its target site, e.g. gram-positive bacteria can change their target site for macrolide, lincosamide and streptogramin B (MLSB) antibiotics through the acquisition of erythromycin resistance methylase (erm) genes.

(e) Active efflux of the antibiotic, reducing intracellular antibiotic concentrations, e.g. the overexpression of one or more efflux systems capable of removing fluoroquinolones and other antibiotic compounds in Pseudomonas aeruginosa.

The genetic determinants of antimicrobial resistance can be located on the bacterial chromosome or on plasmids. Modern DNA techniques such as, automated ribotyping, pulsed field gel electrophoresis (PFGE) and restriction fragment length polymorphism analysis (RFLP) can give us insight into the mechanisms and spread of resistance genes through hospitals and community.

15

Chapter I

Spread and fitness cost of antimicrobial resistance Selection pressure exerted by the heavy use of antimicrobial agents encourages the emergence and the proliferation of resistant strains and has been positively linked to increased rates of antibiotic resistance.26 An important point that needs to be made in this respect is that the increase in antimicrobial resistance rates is not only caused by selection of resistant microorganisms in patients receiving certain specific antibiotics, which can spread to other patients when there are lapses in infection control management, but also by the antibiotic pressure itself, which can increase the frequencies of mutation and horizontal transfer causing increased antimicrobial resistance due to spread of the resistance determinants themselves.27 Another factor to be kept in mind is that the use of antimicrobial agents influences the normal commensal flora of for example the throat and the gastrointestinal tract, which form an important defense mechanism against pathogenic microorganisms.28 On the other hand this ‘normal flora’ should not be idolized too much, because they probably play a role in the horizontal transfer of resistance determinants as well. Although, so far, the latter is still purely speculative, it is a stringent note for a reserved attitude towards the use of selective digestive tract decontamination (SDD) and the use of probiotics in areas with increased resistance rates.24,25

Mutations that render bacteria resistant, frequently occur in genes that fulfil essential functions in protein synthesis.26 It is generally believed that these mutations make the bacterium less fit to compete with its susceptible counterparts and in the absence of the selecting antibiotic pressure the proportion of resistant bacterial cells will gradually decrease. To complicate matters further, this fitness cost can be compensated for by additional mutations.26,30,31

Although it remains difficult to prove that restriction of, or changes in antibiotic selection pressure reduce antimicrobial resistance rates, they are strongly suggested as critical components of the solution in combination with strict infection control measures and active surveillance, which are the principle driving forces behind prevention strategies in the battle against microbial-resistance.32

16

Introduction

Prevention strategies In literature it is advocated that the combination of three primary strategies is required to reduce the emergence and spread of antimicrobial resistance.33 The first consists of increased attention for infection control measures: handwashing still remains the most important and effective infection control measure to prevent horizontal transfer of antimicrobial-resistant pathogens from a colonized patient to a non-colonized patient.34-36 In addition, contact isolation of patients colonized with antibiotic-resistant microorganisms and appropriate usage of gowns and gloves can further reduce the risk of cross-contamination.37,38 Adequate numbers of nurse staffing is always required, because increase of workload in the ICU will inevitably lead to a decline in infection control practices.39 The second strategy is good antibiotic stewardship, meaning the rational use of the appropriate antimicrobial agents on the right indications, at the right dosage and for a sufficient duration of time. Ignorance of these minimal requirements will lead to inappropriate treatment and sub-optimal tissue concentrations, which will increase the risk of antibiotic-resistance. 40-44 The third strategy contains antibiotic-control programs such as formularies and education, combination antibiotic treatment regimens, restriction programs and the rotation of antimicrobial agents. Education programs and practice guidelines for antibiotic prescription have been instituted to avoid unnecessary antibiotic treatment and increase the effectiveness of prescribed antibiotic therapy.45 The use of combination antibiotic therapy, with double coverage, has been suggested as alternative treatment in hospital-acquired infections, however, there is a lack of clinical evidence for this and it has the potential drawback of increasing overall resistance.46 Restriction in the use of certain antibiotics seems most effective during outbreaks of specific bacterial pathogens, it reduces specific antibiotic resistance and it reduces antimicrobial costs.40,47 Antibiotic rotation or the cycling of antibiotic classes has been used to withdraw specific antibiotic drugs from use and to reintroduce them at a later point in time to limit the antibiotic pressure that this cycled antibiotic is

17

Chapter I

exerting on the microbial flora. Several of these studies have reported encouraging results of decreasing, mostly gram-negative, resistance and improvement in clinical outcomes.48-53

The main purpose of these antibiotic control programs is to decrease the emergence of antimicrobial resistance by reducing the selective pressure of specific antibiotic classes, through (periodical) changes in the standard antibiotic regimens of a hospital ward (e.g. ICU). However, only full potential can be achieved in combination with good surveillance programs of antimicrobial resistance and an increased adherence to infection prevention measures by all health care workers.33

The outline of this thesis The world-wide increase of antimicrobial resistance is often ascribed to the excessive usage of broad-spectrum antibiotics in ICU’s exerting selective pressure on bacteria. Therefore, antibiotic-control strategies should include reduction or changes of the antimicrobial selection pressure by restricting or altering the use of antibiotics in order to reduce antimicrobial resistance. The aim of this thesis is to gain more insight into the feasibility and the effect of changes in antibiotic policy on antimicrobial resistance, in a surgical ICU by answering the following questions: 1. Is it possible to influence the antimicrobial treatment duration in patients undergoing open management of the abdomen (OMA) in order to reduce excessive and unnecessary antibiotic utilization ? (Chapter 2) 2. Can we create an objective model to determine outcome and a guideline as to when antimicrobial treatment can be safely stopped in patients undergoing OMA ? (Chapter 3) 3. Does antibiotic cycling change antimicrobial resistance levels in a surgical ICU ? (Chapter 4)

18

Introduction

4. What is the additional value of the routine typing of potential pathogens from surveillance cultures taken in the ICU ? (Chapter 5, 6) 5. What is the impact of antibiotic rotation in a United States medical ICU on Pseudomonas aeruginosa ? (Chapter 7) 6. Can we relate changes in antibiotic resistance levels to (inter-species) transfer of resistance genes ? (Chapter 8)

19

Chapter I

References 1. Low DE, Kellner JD, Wright GD. Superbugs: How they evolve

and minimize the cost of resistance. Curr Infect Dis Rep1999; 1:464-9.

2. Pollard AJ, Dobson SR. Emerging infectious diseases in the 21st century. Curr Opin Infect Dis 2000; 13:265-75.

3. Martone WJ, Nichols RL. Recognition, prevention, surveillance and management of surgical site infections: introduction to the problem and symposium overview. Clin Infect Dis 2001; 33(Suppl 2):S67-S68.

4. Barie PS. Antibitic-resistant gram-positive cocci: implications for surgical practice. World J Surg 1998; 22:118-26.

5. Fry DE. The economic costs of surgical site infection. Surg Infect (Larchmt) 2002; 3(Suppl 1):S37-S43.

6. Flemming A. On the antibacterial action of cultures of a Penicillium, with special reference to their use in the isolation of B. influenzae. Br J Exp Pathol 1929; 10:226-230.

7. Kunin CM. Resistance to antimicrobial drugs: a world-wide calamity. Ann Int Med 1993; 118:557-61.

8. Emmer CL, Besser RE. Combating antimicrobial resistance: intervention programs to promote appropriate antibiotic use. Infect Med 2002; 19:160-173.

9. Weber DJ, Rutala WA. Nosocomial infections in the icu: the growing importance of antibiotic-resistant pathogens. Chest 1999; 115:S34-S41.

10. Albrich WC, Angstwurm M, Bader L, Gartner R. Drug resistance in intensive care units. Infection 1999; 27(Suppl 2):S19- S23.

11. Geissler A, Gerbeaux P, Garnier I, et al. Rational use of antibiotics in the intensive care unit: impact on microbial resistance and costs. Intensive Care Med 2003; 29:49-59.

12. Boyce JM, Pittet D. Guideline for hand hygiene in health-care settings. Am J Infect Control 2002; 30:S1-S46.

20

Introduction

13. Grundman H, Hori S, Winter B, Tami A, Austin DJ. Riskfactors for the transmission of methicillin-resistant Stahylococcus aureus in an adult intensive care unit: fitting a model to the data. J Infect Dis 2002; 185:481-488.

14. Hanberger H, Diekema D, Fluit A, et al. Surveillance of antibiotic resistance in European ICUs. J Hosp Infect 2001; 48:161-76.

15. Richards M, Thursky K, Buising K. Epidemiology, prevalence, and sites of infections in intensive care units. Semin Respir Crit Care Med 2003; 24:3-22.

16. Fluit AC, Verhoef J, Schmitz FJ. Frequency of isolation and antimicrobial resistance of gram-negative and gram-positive bacteria from patients in intensive care units of 25 European university hospitals participating in the European arm of the SENTRY antimicrobial surveillance program 1997-1998. Eur J Clin Microbiol Infect Dis 2001; 20:617-25.

17. Vincent JL, Bihari JD, Suter PM, et al. The prevalence of nosocomial infection in intensive care units in Europe. JAMA 1995; 274:639-44.

18. Livermore DM. Bacterial resistance: Origins, Epidemiology, and impact. CID 2003; 36(Suppl1): S11-S23.

19. Eggimann P, Pittet D. Infection control in the ICU. Chest 2001; 120:2059-93.

20. Cohen ML. Changing patterns of infectious disease. Nature 2000; 406:762-7.

21. McGowan JE jr. Economic impact of antimicrobial resistance. Emerg Infect Dis 2001; 7:286-92.

22. Lawrence RM, Hoeprich PD. Microbial development of drug resistance mechanisms and clinical significance. CRC Crit Rev Clin Lab Sci 1975; 5:365-86.

23. Gold HS, Moellering RC jr. Antimicrobial-drug resistance. N Engl J Med 1996; 335:1445-53.

24. Bonten MJ, Brun-Buisson C, Weinstein RA. Selective decontamination of the digestive tract: to stimulate or stiffle? Intensive Care Med 2003; 29:672-6.

21

Chapter I

25. Borriello SP, Hammes WP, Holzapfel W, et al. Safety of probiotics that contain lactobacilli or bifidobacteria. Clin Infect Dis 2003; 36:775-80.

26. Normark HB, Normark S. Evolution and spread of antibiotic resistance. J Int Med 2002; 252:91-106.

27. Schmitz FJ, Fluit AC. Mechanisms of resistance. In: Armstrong D, Cohen J (eds) Infectious Diseases. Harcourt Publishers Ltd 1999. Section 7 Chapter 2 pp1-14.

28. Austin DJ, Kristinsson KG, Anderson RM. The relationship between the volume of antimicrobial consumption in human communities and the frequency of resistance. Proc Natl Acad Sci USA 1999; 96:1152-6.

29. Heinemann JA. How antibiotics cause antibiotic resistance. Drug Discov Today 1999; 4:72-9.

30. Fluit AC, Schmitz FJ. Bacterial resistance in urinary tract infections: how to stem the tide. Exp Opin Pharmacother 2001; 2:813-8.

31. Tønjum T, Seeberg E. Microbial fitness and genome dynamics. Trends Microbiol 2001; 9:356-8.

32. Monroe S, Polk R. Antimicrobial use and bacterial resistance. Curr Opin Microbiol 2000; 3:496-501.

33. Shlaes DM, Gerding DN, John JF Jr, et al. Society for healthcare epidemiology of America and infectious diseases society of America joint committee on the prevention of antimicrobial resistance: guidelines for the prevention of antimicrobial resistance in hospitals. CID 1997; 25:584-99.

34. Jarvis WR. Handwashing-the Semmelweis lesson forgotten? Lancet 1994; 344:1311-2.

35. Austin DJ, Bonten MJ, Weinstein RA, Slaughter S, Anderson RM. Vancomycin-resistant enterococci in intensive-care hospital settings: transmission dynamics, persistence, and the impact of infection control programs. Proc Natl Acad Sci U S A. 1999 Jun 8;96(12):6908-13.

36. Teare L, Cookson B, Stone S. Hand hygiene. Use of alcohol hand rubs between patients:they reduce the transmission of infection. BMJ 2001; 323:411-12.

22

Introduction

37. Weinstein RA. Controlling antimicrobial resistance in hospitals: infection control and use of antibiotics. Emerg Infect Dis 2001; 7:188-92.

38. Puzniak LA, Leet T, Mayfield J, Kollef M, Mundy LM. To gown or not to gown: the effect on acquisition of vancomycin-resistant Enterococci. CID 2002; 35:18-25.

39. Grundman H, Hori S, Winter B, Tami A, Austin DJ. Riskfactors for the transmission of methicillin-resistant Stahylococcus aureus in an adult intensive care unit: fitting a model to the data. J Infect Dis 2002; 185:481-88.


41. Singer MV, Haft R, Barlam T, et al. Vancomycin control measures at a tertiary-care hospital: impact of interventions on volume and patterns of use. Infect Control Hosp Epidemiol 1998; 19:248-53.

42. Gerding DN. Good antimicrobial stewardship in the hospital: fitting, but flagrantly flagging. Infect Control Hosp Epidemiol 2000; 21:253-5.

43. Bell DM. Promoting appropriate antimicrobial drug use: perspective from the centers for disease control and prevention. CID 2001; 33(Suppl 3):S245-S250.

44. Fridkin SK, Lawton R, Edwards JR, et al. Monitoring antimicrobial use and resistance: comparison with a national benchmark on reducing vancomycin use and vancomycin- resistant Enterococci. Emerg Infect Dis 2002; 8:702-7.

45. Murthy R. Implementation of strategies to control antimicrobial resistance. Chest 2001; 119:405S-411S.

46. Kollef MH, Fraser VJ. Antibiotic resistance in the intensive care unit. Ann Int Med 2001; 134:298-314.

47. Leverstein-van Hall MA, Fluit AC, Blok HEM, et al. Control of nosocomial multiresistant Enterobacteriaceae using a temporary restrictive antibiotic agent policy. Eur J Microbiol Infect Dis 2001; 20:785-91.

23

Chapter I

48. Gerding DN, Larson TA, Hughes RA, et al. Aminoglycoside resistance and aminoglycoside usage: ten years of experience in one hospital. Antimicrob Agents Chemother 1991; 35:1284-90.

49. Kollef MH, Vlaskin J, Sharpless L, et al. Scheduled changes of antibiotic classes. A strategy to decrease the incidence of ventilator-associated pneumonia. Am J Respir Crit Care Med 1997; 156:1040-8.

50. Dominguez EA, Smith TL, Reed E, et al. A pilot study of atibiotic cycling in a hematology-oncology unit. Infect Control Hosp Epidemiol 2000; 21(Suppl.):S4-S8.

51. de Man P, Verhoeven BAN, Verburgh HA, Vos MC, van den Anker. An antibiotic policy to prevent emergence of resistant bacilli. Lancet 2000; 355:973-8.

52. Gruson D, Hilbert G, Vargas F, et al. Rotation of antibiotics in a medical intensive care unit. Am J Resp Care Med 2000; 162:837-43.

53. Raymond DP, Pelletier SJ, Crabtree TD, et al. Impact of rotating empiric antibiotic schedule on infectious mortality in an intensive care unit. Crit Care Med 2001; 29: 1101-8.

24

Introduction

25

Chapter I

26

Chapter II

Short versus Prolonged Antimicrobial Treatment during Open Management

of the Abdomen.

A Randomized Clinical Trial.

H.J. van Loon, K. Bosscha, M.R. Visser, A. Algra, J. Verhoef and Chr. van der Werken

Submitted for publication

Chapter II

Abstract The effectiveness of short versus prolonged antimicrobial therapy was compared in patients undergoing open management of the abdomen (OMA). Between February 1996 and June 2002 all patients with a persisting intra-abdominal infection requiring OMA were randomized to receive either five days (Group A) or a minimum of eight days (Group B) of antibiotic treatment. Primary outcome measures were recurrence of abdominal sepsis, or intra-abdominal abscess and mortality. Secondary outcome measures were the development of several clinical parameters (APACHE II, MPI, Bone criteria), the occurrence of complications and the duration of hospital stay. A total of 56 patients could be evaluated, 26 in Group A and 30 in Group B. Abdominal sepsis recurred in 4 patients of Group A and 9 patients of group B (RR 0.51; 95%CI 0.18-1.47). Twenty-four patients died (43%), 12 in each group. There were no major differences in the development of clinical parameters and complications, while hospital stay was longer in Group B (P=0.02). Unfortunately we were unable to produce convincing evidence to determine differences in duration of antibiotic treatment due to the limited size of this study and the large number of patients in Group A with persisting life threatening conditions warranting prolonged antibiotic use. However, this randomized clinical trial did show how difficult it is to enforce short antibiotic treatment in patients undergoing OMA, and hopefully future multi-center studies can acquire sufficient numbers of patients to bypass the problems encountered during this study.

28

Short vs Prolonged Antimicrobial Treatment

Introduction In selected cases, open management of the abdomen (OMA) is the treatment of choice for persisting secondary peritonitis.1,2 This procedure of repeated laparotomies with drainage of the peritoneal cavity is generally combined with prolonged broad-spectrum antibiotic therapy.3-6 Although the therapeutic value of antibiotics is clear, there is still little consensus on the duration of antimicrobial treatment in patients with an established intra-abdominal infection.7-9 The duration of antibiotic treatment is commonly determined by parameters such as body temperature and white blood cell count, often leading to prolonged treatment duration.10,11 Considering the open peritoneal cavity to be a drained abscess, one can discuss the role of prolonged antibiotic administration. The aim of this randomized clinical trial was to assess the effectiveness of short compared to prolonged administration of antibiotics in patients undergoing OMA. Patients and Methods Patients Between February 1996 and June 2002, all patients in the Surgical Intensive Care Unit (SICU) undergoing OMA were prospectively included in this study. Patients were excluded if they were < 18 years, had an Acute Physiology and Chronic Health Evaluation II-score (APACHE II-score) > 25 or had multiple organ failure (MOF) prior to admission on our SICU. The day OMA started was considered as the index day (day 0). After receiving written informed consent, patients were randomized into two groups, receiving short (Group A) or prolonged (Group B) antibiotic treatment. Consecutive numbered envelopes, containing the designated group, were drawn to perform randomization. The protocol was approved by the Medical Ethical Committee (METC) of the University Medical Center Utrecht (UMCU), The Netherlands.

29

Chapter II

Surgical management Open management of the abdomen consisted of planned re-explorations, every other day, with systematic lavage of the peritoneal cavity. A mesh was used to cover the peritoneal cavity in between re-explorations. For superficial drainage, suction tubes with multiple side holes were placed across the mesh and the open abdomen was covered with a transparent drape, to form a water-tight seal.12 This procedure was repeated until the peritoneal cavity was macroscopically clean of infectious debris and closure of the abdominal wall was possible. Antimicrobial treatment groups In Group A patients received standard antibiotic treatment for five days. Only in the case of persisting severe sepsis, according to the criteria defined by Bone et al. (Table1), antibiotics were continued.13 In Group B, antibiotic treatment was continued for at least eight days, after which administration was only discontinued when there were no more than two sepsis-criteria present.

Criteria

Temperature > 38 0C or < 36 0C Heart rate > 90 beats per minute Respiratory rate > 20 breaths per minute or PaCO2 < 32 mm Hg White blood cell count > 12000/cu mm

Manifested sepsis with two or more criteria. Severe sepsis: Manifested sepsis in combination with organ dysfunction, hypoperfusion, or hypotension. Table1: Sepsis criteria according to Bone et al.13

30


Microbiology Peritoneal cultures were obtained during every re-operation and studied according to standard microbiological methods. Initial broad-spectrum antibiotics were either started blindly or depended on previous abdominal culture results. They included mono-therapy or combinations of imipenem or other carbapenems, aminoglycosides, fluoroquinolones and ß-lactam / ß-lactamase inhibitor combinations, metronidazole and anti-fungal agents. Antibiotics were adjusted according to reported susceptibility patterns. Data collection and outcome measures Data on patients� demographics including age, sex, medical history, source and duration of abdominal sepsis were collected. Clinical parameters as the APACHE II-score to describe the development of the patient�s physiological state, the Mannheimer Peritonitis index (MPI) as measure of intra-abdominal infection and the criteria according to Bone et al. to ascertain the severity of sepsis were recorded every other day from day 0 on.13-16 Subsequent blood samples were taken for laboratory testing. Primary outcome measures were recurrence of abdominal sepsis, or intra-abdominal abscesses after discontinuation of initial antibiotic therapy, as well as in-hospital mortality. Secondary outcome measures were the development of the APACHE II, MPI and Bone sepsis scores (including white blood cell count), the occurrence of local or systemic complications and the duration of hospital stay. Guidelines from the Centers for Disease Control (CDC) were used to define primary and secondary outcome measurements.17,18

31

Chapter II

Statistical analysis Taking into account the small number of OMA patients admitted to our Surgical Intensive Care Unit (SICU) per year, we decided to analyze the difference in leukocytes, from blood samples taken on the day of antibiotic cessation, as a proxy-endpoint. Assuming a difference of 4 x 109/L to be clinically relevant, a standard deviation (SD) for leukocytes of 4 x109/L, α = 0.05 and β = 0.02, a sample size of 50 patients was calculated. Statistical analysis was performed with SPSS (Chicago, IL) and Confidence Interval Analysis (CIA, Br Med J, London). Between group differences for continuous variables were assessed with the unpaired t-test. The frequencies of dichotomous outcomes were compared with the chi-square test, calculation of the relative risk (RR) and their accompanying 95 % confidence intervals (95%CI). Differences in primary and secondary outcome measures were analyzed on an intention-to-treat basis, i.e. if antibiotic treatment had to be continued in Group A, because of persisting severe sepsis, these patients were analyzed according to their original treatment allocation. Data was expressed as mean ± SD unless specified otherwise. Results Population Characteristics A total of 60 consecutive patients undergoing OMA for persisting secondary peritonitis, were included. Twenty-eight patients were randomized to Group A and 32 to Group B (Fig.1). Sufficient data to properly assess clinical outcome failed in four cases (2 Group A and 2 Group B) and they were considered no further. Fifty-six patients remained for analysis on the basis of the intention to treat principle: twenty-six in Group A and 30 in Group B. Baseline characteristics were similar among the groups (Table 2). OMA was indicated in 22 patients (39 %) for perforation of the digestive tract (10 Group A and 12 Group B), 24 (43 %) for anastomotic disruptions (11 Group A and

32


Characteristics

Group A ( n = 26 )

Group B ( n = 30)

Male, n 13 15 Age, mean ± SD, y 58.1 ± 16 56.5 ± 16 Medical history Cardiac tract, n 6 9 Respiratory tract, n 5 2 Digestive tract, n 14 18 Urogenital tract, n 10 16 Neurologic tract, n 2 5 Endocrine tract, n 1 1 Psychiatric, n 2 4 Indication for OMA* Small bowel perforation, n (%) 5 (19) 6 (20) Colon perforation, n (%) 5 (19) 6 (20) Anastomotic leakage, n (%) 11 (42) 13 (43) Pancreatitis, n (%) 5 (19) 5 (16) APACHE II-score day 0, median (IQR)# 11 (8.8-14) 11 (9-14.3) Mannheim � score day 0, median (IQR)# 32 (25.8-34.5) 31 (25.8-32.3) Bone � Criteria day 0, median (IQR)# 2 (2-3) 3 (3-3) Days of antibiotic treatment, mean (range) 13 (1-26) 17 (8-41) Explorations during OMA*, mean (range) 6 (2-13) 8 (2-31) Days ventilatory support, mean (range) 23 (8-62) 31 (12-78) Days parenteral nutrition, mean (range) 16 (5-44) 23 (9-53) * OMA: Open Management of the Abdomen. # IQR: Interquartile Range. Table 2: Population characteristics.

33

Chapter II

13 Group B) and for 10 (18 %) cases of necrotizing pancreatitis (5 Group A and 5 Group B). At the start of OMA the physiologic state, the severity of intra-abdominal infection and the severity of sepsis were similar in both groups. The mean duration of antibiotic treatment in Group A was 13 ± 7 days. In only six patients it was possible to actually stop antibiotics on day 5. Two patients had already died within the first three days, while 13 patients had to continue antibiotic therapy because of persisting severe abdominal sepsis and five due to pneumonia (Fig.1). In Group B all patients received antibiotics for at least eight days, with a mean duration of treatment of 17 ± 9 days. This made the between group difference only 4 days and therewith not statistically significant (95%CI -0.8-8.3). Short Prolonged N = 28 N = 32 2 Missing Data 2 Missing Data N = 26 N = 30 2� < Day 5 N = 24 4 AB stop = Day 8 26 AB > Day 8

6� Abd. Sepsis 6� Complication

6 AB stop = Day 5 18 AB > Day 5 3�

13 Persisting Abd. Sepsis 5 Complication 5� 2�

N=60

Figure 1: Flow diagram of the progress through the phases of the trial.

34


Primary outcome measures In four patients (15 %) in Group A abdominal sepsis recurred after their antibiotics were stopped, compared to nine (30 %) in Group B (Table 3). The relative risk for the primary outcome was 0.51 (95%CI 0.18-1.47). The recurrence rate of intra-abdominal abscess was seven (27 %) in Group A and 12 (40 %) in Group B (RR 0.67; 95%CI 0.31-1.45). Twenty-four patients (43 %) died, 12 in both groups. The main cause of death was multiple organ failure, resulting in 7 deaths in Group A and 6 in group B. The other deaths in Group A were due to a cerebral hemorrhage, one case of Adult Respiratory Distress Syndrome (ARDS), two cases of Myocardial Infarction (MI) and one patient having an anaphylactic shock induced by intravenous radiological contrast agent. In Group B the additional deaths were caused by pulmonary emboli and toxic encephalopathy respectively in one case each, ARDS and major gastrointestinal hemorrhages in two cases each.

Primary outcomes

Group A N=26

Group B N=30

Relative Risk

CI 95%

Recurrent abd. sepsis, n (%) 4 (15) 9 (30) 0.51 0.18-1.47 Recurrent abd. abscess, n (%) 7 (27) 12 (40) 0.67 0.31-1.45 Mortality, n (%) 12 (46) 12 (40) 1.15 0.63-2.11

Table 3: Comparison of primary outcomes between the short and prolonged treatment groups.

35

Chapter II

Secondary outcomes

Group A N=26

Group B N=30

Relative Risk

CI 95%

Urinary tract infection, n (%) 5 (19) 4 (13) 1.44 0.43-4.81 Pneumonia, n (%) 15 (58) 15 (50) 1.15 0.71-1.88 Central catheter infection, n (%) 7 (27) 13 (43) 0.62 0.29-1.32 Bleeding, n (%) 3 (12) 6 (20) 0.58 0.16-2.08 Fistula formation, n (%) 2 (8) 6 (20) 0.39 0.09-1.74 Hospital stay, days, mean ± SD 35 ± 20 61 ± 55 26* 4-49 SICU stay, days, mean ± SD 25 ± 15 35 ± 26 10* -1-22

Table 4: Comparison of secondary outcomes between the short and prolonged treatment groups. SICU: Surgical Intensive Care Unit. * Mean difference. Secondary outcome measures The evolvement of the clinical parameters, APACHE II, MPI and Bone criteria, monitored from day 0 until day 30, showed no differences between the groups (Fig.2). More than half (54%) of our study population developed pneumonia and was subsequently treated with antibiotics. Central catheter infection was observed in 7 patients of Group A and 13 patients of Group B. Nine patients suffered from intra-abdominal bleeding. In two patients duodenal perforation became fatal after profuse bleeding. Fistulas, developing within 30-40 days after cessation of antibiotics, were observed in eight patients, two in Group A and six in Group B (RR 0.39; 95%CI 0.09-1.74). Analysis revealed that patients having a fistula, had undergone more laparotomies, 11.3 ± 8.1 compared to 6.6 ± 3.5 (difference 4.7; 95%CI 1.3-8.0). Mean hospital stay of the total study population, calculated from day 0, was 35 ± 20 days in Group A compared to 61 ± 55 days in Group B. The independent samples t-test showed the difference of 26 days to be statistically significant (95%CI 4-49). Mean SICU stay tended to be longer in Group B (35 days) than in Group A (25 days); mean difference 10 days (95%CI �1-22).

36


Proxy-endpoint The day patients were discontinued from their antibiotics, morning blood samples revealed a mean white blood cell count of 13.0 ± 4.4 x 109/L in Group A, compared to 17.4 ± 6.6 x 109/L in Group B; mean difference 4.4 (95%CI 0.97-7.8). Discussion This randomized clinical trial was designed in an attempt to evaluate the efficacy of short compared to prolonged antibiotic treatment in patients with severe secondary peritonitis, undergoing OMA. Unfortunately, there were many patients in Group A with a persisting severe sepsis on day 5, according to the sepsis criteria (Fig.1). In 13 of these patients an abdominal sepsis persisted and five had infectious complications of other than abdominal origin, which also needed antibiotic therapy. This resulted in a statistically non-significant difference in the mean duration of antibiotic treatment between the two groups. Even after exclusion of the patients with prolonged antibiotic treatment in Group A, we found no statistically significant differences in primary outcomes, neither in the recurrence of abdominal sepsis, nor intra-abdominal abscess and mortality, after short (Group A; basically 5 days) or prolonged (Group B; at least 8 days) antibiotic treatment. These data are consistent with previous reports suggesting treatment durations of 5-9 days.4,5,8,19-21 The limited size of this study is a reflection of the small number of patients treated with OMA in our SICU. This resulted in a limited precision of the effect estimates for the primary outcome measures. For the proxy-endpoint, however, we found a statistically significant difference in white blood cell count, highest in Group B (mean difference 4.4; 95%CI 0.97-7.8). This could implicate white blood cell count to be an unreliable parameter, as suggested in other studies, leading to unjustified prolongation of antimicrobial treatment when used as

37

Chapter II

parameter for antibiotic therapy in combination with elevated body temperature.10,11

Eight patients developed an entero-cutaneous fistula; all became apparent after antibiotics had been stopped, which might suggest that prolonged antibiotic therapy can mask clinical signs of chronic abscess, with risk of fistula formation.22 All patients with a fistula had undergone several more laparotomies (difference 4.7; 95%CI 1.3-8.0), which confirms that repeated manipulation of the bowel increases the risk of fistula formation.23,24 Subsequently, the patients with a fistula in Group B could explain for the prolonged hospital stay in Group B, compared to Group A (difference 26 days; 95%CI 4-49). Conclusion This randomized clinical trial showed how difficult it is to enforce short antibiotic treatment in patients undergoing OMA. Although the protocol determined that antibiotic treatment had to be stopped after five respectively after at least eight days, we were unable to create two comparable groups with a statistically significant difference in duration of antibiotic treatment, because too many patients suffered from life threatening conditions warranting prolonged use of antibiotic therapy. Thus, even in view of the known drawbacks of prolonged antibiotic therapy such as toxicity, antimicrobial resistance development and costs, our study demonstrated that the duration of antibiotic treatment in patients with severe peritonitis will remain individually based, because every patient shows his or her specific development of clinical parameters and risk factors.25-27 Reducing antibiotic therapy in patients undergoing OMA to in principle 5 days will be a worthwhile aim, although the question remains if this is feasible in daily practice. Eventually, future multi-center studies with sufficiently large study populations will be needed to make possible differences between short and prolonged antibiotic treatment more convincing.

38


References 1. Schein M. Surgical management of intra-abdominal infection: is

there any evidence. Langenbecks Arch Surg 2002; 387: 1-7. 2. Bosscha K, van Vroonhoven JMV, van der Werken Chr. Surgical

management of severe secondary peritonitis. Br J Surg 1999; 86: 1371-7.

3. Wittmann DH, Schein M, Condon RE. Management of secondary peritonitis. Ann Surg 1996; 224: 10-8.

4. Berger D, Buttenschoen K. Management of abdominal sepsis. Langenbecks Arch Surg 1998; 383: 35-43.

5. Cornwell EE 3rd, Dougherty WR, Berne TV et al. Duration of antibiotic prophylaxis in high-risk patients with penetrating abdominal trauma: a prospective randomized trial. J Gastrointest Surg 1999; 3: 648-53.

6. Wittmann DH, Wittmann-Tylor A. Scope and limitations of antimicrobial therapy of sepsis in surgery. Langenbecks Arch Surg 1998; 383: 15-25.

7. Dellinger EP. Undesired effects of antibiotics and future studies. Eur J Surg Suppl 1996; 576: 29-32.

8. Bohen JMA. Postoperative peritonitis. Eur J Surg Suppl 1996; 576: 50-2.

9. Alcocer F, Lopez E, Calva JJ, Herrera MF. Antibiotic treatment in secondary peritonitis: towards a defenition of its optimal duration. Rev Invest Clin 2001; 53: 121-5.

10. Solomkin JS, Reinhart HH, Dellinger EP et al. Results of a randomized trial comparing sequential intravenous/ oral treatment with ciprofloxacin plus metronidazole to imipenem/cilastatin for intra-abdominal infections. Ann Surg 1996; 223: 303-15.

11. Lennard ES, Dellinger EP, Wertz MJ, Minshew BH. Implications of leukocytosis and fever at conclusion of antibiotic therapy for intra-abdominal sepsis. Ann Surg 1982; 195: 19-24.

12. Bosscha K, Hulstaert PF, Visser MR, van Vroonhoven TJ, van der Werken C. Open management of the abdomen and planned reoperations in severe bacterial peritonitis. Eur J Surg 2000; 166: 44-9.

39

Chapter II

13. Bone RC, Balk RA, Cerra FB et al. Definitions of sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Chest 1992; 101: 1644-55.

14. Nyström PO, Bax R, Dellinger EP et al. Proposed definitions for diagnosis, severity scoring, stratification, and outcome for trials on intra-abdominal infection. World J Surg 1990; 14: 148-58.

15. Ivatury RR, Nallathambi M, Rao PM, Rohman M, Stahl WM. Open management of the septic abdomen: therapeutic and prognostic considerations based on APACHE II. Crit Care Med 1989; 17: 511-17.

16. Linder MM, Wacha H, Feldmann U et al. The Mannheim peritonitisindex. An instrument for the intraoperative prognosis of peritonitis. Chirurg 1987; 58: 84-92.

17. Garner JS, Jarvis WR, Emori TG, Horan TC, Hughes JM. CDC definitions for nosocomial infections,1988. Am J of Inf Control 1988; 16: 128-40.

18. Horan TC, Gaynes RP, Martone WJ, Jarvis WR, Emori TG. CDC definitions of nosocomial surgical site infections, 1992: A modification of CDC definitions of surgical wound infections. Infect Control Hosp Epidemiol 1992; 13: 606-8.

19. Runyon BA, McHutchison JG, Antillon MR, Akrividis EA, Montano AA. Short-course versus long-course antibiotic treatment of spontaneous bacterial peritonitis: a randomized controlled study of 100 patients. Gastroenterology 1991; 100: 1737-42.

20. Schein M, Wittmann DH, Lorenz W. Forum statement: a plea for selective and controlled postoperative antibiotic administration. Eur J Surg Suppl 1996; 576: 66-9.

21. Nathens AB, Rotstein OD. Antimicrobial therapy for intra-abdominal infection. Am J Surg 1996; 172(6A): S1-S6.

22. Bonfils REA, Nealon TF. Subphrenic abscess:comparison between operative and antibiotic management. Ann Surg 1974; 180: 209-12.

23. Goor H, Hulsebos RG, Bleichrodt RP. Complications of planned relaparotomy in patients with severe general peritonitis. Eur J Surg 1997; 163: 61-6.

40


24. Hau T, Ohmann C, Wolmershäuser A, Wacha H, Yang Q. Planned relaparotomy vs relaparotomy on demand in the treatment of intra-abdominal infections. Arch Surg 1995; 130: 1193-97.

25. Saadia R, Lipman J. Duration of antibiotic treatment in surgical infections. Antibiotics and the gut. Eur J Surg Suppl 1996; 576: 39-41.

26. Wittmann DH, Schein M. Let us shorten antibiotic prophylaxis and therapy in surgery. Am J Surg 1996; 172(6A): S26-S32.

27. Montravers P, Gauzit R, Muller C et al. Emergence of antibiotic-resistant bacteria in cases of peritonitis after intra-abdominal surgery affects the efficacy of empirical antimicrobial therapy. Clin Infect Dis 1996; 23: 486-94.

41

Chapter II

Appendix A 30 20 10

2315 2517 2623 3024 3024 3026N =

APACHE II score

Group BGroup A

0

-10

Day 5

Day 8

Day 14

Dag 25

Day 30

D5

D8

D14

D25

D30

D0D5 D8

D14D25 D30

D0D5 D8

D14 D25 D30

D0 Day 0

Development of the APACHE II-score from day 0 to day 30. The black boxes represent the interquartile range on the different days of measurement, containing 50% of the values. The whiskers are lines that extend from the boxes to the highest and lowest values. The white lines across the boxes indicate the median. The numbers along the horizontal axis indicate the living patients in each group. The vertical axis illustrates the number of points for the score.

42


Appendix B 50

40

30 20

10

1312 2212 2924 3026N =

Mannheimer Peritonitis Index ( MPI )

Group BGroup A

0

Day 0

Day 5

Day 8

Day 14

D0 D0D0

D5 D5

D5D8

D8

D14

D14

D14D25

Development of the Mannheimer Peritonitis Index (MPI) from day 0 to day 14*. The black boxes represent the interquartile range on the different days of measurement, containing 50% of the values. The whiskers are lines that extend from the boxes to the highest and lowest values. The white lines across the boxes indicate the median. The numbers along the horizontal axis indicate the living patients still having re-explorations in each group. The vertical axis illustrates the number of points for the score. * There were insufficient data on MPI beyond day 14.

43

Chapter II

Appendix C

2315 2517 2623 3024 3024 3026N =

Sepsis criteria

Group BGroup A

5

4

3

2

1

0

-1

Day 0

Day 5

Day 8

Day 14

Day 25

Day 30

D0

D0

D0

D0 D0D5

D5D5

D8

D8

D8

D14

D14D14 D25 D25

D25

D30 D30

D30

Development of the sepsis criteria from day 0 to day 30. The black boxes represent the interquartile range on the different days of measurement, containing 50% of the values. The whiskers are lines that extend from the boxes to the highest and lowest values. The white lines across the boxes indicate the median. The numbers along the horizontal axis indicate the living patients in each group. The vertical axis illustrates the number of points for the score.

44


45

Chapter II

46

Chapter III

Predicting for Recurrence of Abdominal Sepsis and Mortality in Patients During

Open Management of the Abdomen.

H.J.van Loon, A. Algra, K.Bosscha, M.R. Visser, J. Verhoef and Chr. van der Werken

Submitted for publication

Chapter III

Abstract During the last decades scoring systems such as the Adult Physiology and Chronic Health Evaluation II (APACHE II) and the Mannheimer Peritonitis Index (MPI) have been used to predict outcome in patients with secondary peritonitis. In a previous study we described the Predictor Recurrence Abdominal Sepsis Open Management-score (PRASOM-score), to serve as an indication as to when parenteral antibiotic therapy can be safely discontinued in patients treated with open management of the abdomen (OMA). The aim of the current study was to validate the PRASOM-score with prospectively collected data and to evaluate individual prognostic values in patients with severe secondary peritonitis undergoing OMA. We studied 56 patients treated with OMA for persisting severe secondary peritonitis and performed univariate and multivariate analysis for the development of four predictive models. Receiver-operator characteristic (ROC) curves were used to compare the information content of the new models with that of the PRASOM, APACHE II and the MPI. Decreased blood albumin levels below 23 g/L were related to an increased risk in recurrence of abdominal sepsis on the day antibiotics were stopped and showed better prediction compared with the PRASOM-score. All models derived from our multivariate data performed better, showing ROCs with larger areas under the curve. Although our models showed better predictive values in comparison with the existing scoring systems, they were derived from a small dataset and will have to be validated in a larger patient population. Nevertheless, our findings indicate that there is room for improvement in developing prognostic scoring systems for patients with severe secondary peritonitis.

48

Prediction of Recurrent Sepsis and Mortality

Introduction Secondary peritonitis remains a cause of severe morbidity and is still associated with high mortality of around 30% despite improvements in surgical techniques, the introduction of potent antibiotics and advances in intensive care management.1-3 Open management of the abdomen (OMA), in combination with broad-spectrum antibiotics, has become accepted for the treatment of selected cases of secondary peritonitis, especially when there is insufficient, or doubt about, initial source control after primary laparotomy. The advantages of OMA are easy access for repeated inspections with irrigation and drainage of either persisting or recurring intra-abdominal abscesses and early detection of intra-abdominal complications.4-6 The evaluation of the results of OMA is difficult, because of differences in underlying diseases and the lack of consensus concerning the duration of antibiotic treatment.7,8 During the last decades several scoring systems have been used to predict outcome in patients with severe peritonitis and intra-abdominal infections, for example the Adult Physiology and Chronic Health Evaluation II (APACHE II) and the Mannheimer Peritonitis Index (MPI).9 No published study examined these scoring systems in patients specifically undergoing OMA. In 1998 we described the Predictor Recurrence Abdominal Sepsis Open Management-score (PRASOM-score) that predicted the risk of recurrence of abdominal sepsis in patients treated with OMA on the day of antibiotic cessation (Table 1).10 A score of six points or more was associated with a significantly higher recurrence rate of abdominal sepsis after discontinuation of antimicrobial agents compared to patients with a score of 0-3 points (P<0.001). The goal of the current study was to validate the PRASOM-score with prospectively collected data and to compare this scoring system with the existing APACHE II and MPI scores.

49

Chapter III

Variable

0

score 1

2

Body temperature ≤37.5 37.6-38.5 ≥38.5

Leukocytes (x109/L) <10 10.5-15.5 >15.5

Band cells (%) 0-3 4-9 ≥10

Cause of peritonitis Perforation Disruption Pancreatitis

Duration of initial antibiotics (days) >20 11-20 1-10

Dependant on inotropic agents No - Yes

Table 1: Predictor Recurrence Abdominal Sepsis Open Management-score (PRASOM).

50


Patients and Methods We prospectively studied 56 patients treated with OMA for persisting severe secondary peritonitis, in the surgical intensive care unit (ICU) of the University Medical Center Utrecht, The Netherlands, between February 1996 and June 2002. These patients were part of a randomized controlled trial comparing short versus prolonged antibiotic treatment in patients undergoing OMA.11

Based on underlying disease three groups were distinguished: anastomotic dehiscence (n=24), perforation of the digestive tract (n=22) and necrotizing pancreatitis with secondary infection (n=10). Surgical management consisted of planned re-laparotomies every 24 to 72 hours until the peritoneal cavity was macroscopically clean of infectious debris and closure of the abdominal wall was practically possible. Between these laparotomies the peritoneal cavity was covered with a mesh and a transparent drape to form a water-tight seal.12 Patients were randomized into groups either to receive short (in principle five days) or prolonged (at least eight days) parenteral broad-spectrum antimicrobial treatment from the start of OMA. Within each of these treatment strategies duration of antibiotic treatment was frequently adjusted and prolonged in accordance with clinical response and the results of microbiological cultures with susceptibility patterns. Follow-up was until death or discharge from the surgical ward. Of all patients a case history, previous illness, risk factors and clinical parameters were recorded. The primary endpoints of this study were recurrence of abdominal sepsis and mortality. Recurrence of abdominal sepsis was defined according to the CDC definitions of nosocomial surgical site infections and the 1992 sepsis consensus definitions.13 The main criteria of interest were the PRASOM, APACHE II, and the MPI calculated within the first 24h of ICU treatment and on the day of antibiotic discontinuation. For calculation of the APACHE II score a fixed value of 15 was taken for the Glasgow Coma Scale (GCS), because all patients were sedated and mechanically ventilated. This resulted in 0 points for GCS in all patients that could be added to the APACHE II score.

51

Chapter III

The MPI was discarded for prediction of recurrence of abdominal sepsis or mortality after discontinuation of antimicrobial agents, because in most cases reliable information from re-laparotomy on the day of antibiotic cessation was not available. Descriptive statistics were expressed as percentages for qualitative data and mean ± standard deviation (SD) for quantitative data, unless specified otherwise. Variables from univariate analysis of baseline characteristics, in relation to outcome, were selected if p ≤ 0.25. These variables were sequentially entered in a multivariate Cox proportional hazards model until no variable remained to be entered at the significance level of 0.10. This method was used for the development of three predictive models. They evaluated the risk of recurrence of abdominal sepsis and the risk of death based on the data available when antibiotics were discontinued, and based on the data available within the first 24h of OMA. Receiver-operator characteristic (ROC) curves, calculated on the basis of logistic regression models containing the same set of variables derived during Cox modeling, were used to compare the information content of the new models with that of the PRASOM, APACHE II and the MPI. The more a ROC curve is located in the upper left corner, i.e. the larger its area under the curve (AUC), the higher both the sensitivity and specificity of the models are.

52


Results Patients At the start of OMA the mean age of the 28 men and 28 women was 57.3 ± 15.6 years (range 22-80). Eleven patients still received antibiotics at the moment they died, leaving 45 patients for the evaluation of recurrence of abdominal sepsis and mortality after cessation of the antibiotics. In thirteen patients (29%) abdominal sepsis recurred after discontinuation of antimicrobial agents: one in the pancreatitis group, seven in the anastomotic dehiscence group and five in the perforation group (Table 2). The mean number of re-explorations was 7.2 ± 4.6 and the mean duration of antibiotic treatment was 14.9 ± 8.7 days. There was no statistically significant difference in the number of re-laparotomies or days of antibiotic treatment between patients with a recurrent abdominal sepsis and those without. Microbiological cultures taken at the start of OMA did not reveal significant differences according to the cause of OMA with respect to prevalence of colonization and antimicrobial resistance of specific microorganisms. Twenty-four patients died (24/56) from the following: (13) multiple organ failure (MOF), (3) adult respiratory distress syndrome (ARDS), (2) major gastrointestinal bleeding, (2) myocardial infarctions, one cerebral hemorrhage, one pulmonary emboli, one toxic encephalopathy and one anaphylactic shock induced by intravenous radiological contrast agent. The mean age of the non-survivors was 61.4 ± 12.4 years, with a gender distribution of 14 male and 10 female patients. The survivors had a mean age of 54.2 ± 17.1 years. This was not statistically significantly different from the non-survivors. The mean duration of follow-up until death or discharge was 48.6 ± 43.9 days. Patients who died spent a mean of 26.3 ± 23.6 days in the ICU. The mean length of ICU and hospital stay for survivors were 26.3 ± 16.4 and 61.9 ± 47.7 days, respectively.

53

Chapter III

Pancreatitis dehiscense Perforation Total Patients, n 10 24 22 56 Gender, male (%) 5 (50) 15 (63) 8 (36) 28 (50) Age, y, mean ± sd 52.1 ± 19.1 60.0 ± 12.7 56.6 ± 16.7 57.3 ± 15.6 APACHE -II score, mean ± sd 13.7 ± 5.6 11.4 ± 4.1 11.1 ± 3.3 11.7 ± 4.2 Mannheim score, mean ± sd 29.1 ± 4.8 30.6 ± 7.3 30.0 ± 5.4 29.9 ± 6.2 PRASOM score, mean ± sd 10.1 ± 1.4 7.9 ± 1.7 6.7 ± 1.8 7.8 ± 2.0 Laparotomies, mean ± sd 7.3 ± 4.2 7.7 ± 5.7 6.7 ± 3.5 7.2 ± 4.6 Duration AB, days, mean ± sd 16.8 ± 13.5 14.5 ± 7.8 14.4 ± 7.1 14.9 ± 8.7 Prevalence of colonization day 1-5 Enterobacteriaceae, n (R) 1 (1) 18 (2) 17 (2) 36 (5) Staphylococcus aureus, n (R) 0 0 2 (0) 2 (0) Enterococcus spp., n (R) 2 (0) 13 (4) 13 (3) 28 (7) CNS , n (R) 7 (5) 12 (9) 8 (7) 27 (21) Candida spp., n (R) 2 (2) 12 (7) 12 (9) 26 (18) Recurrence after AB discontinuation (n=45) Recurrent abd. sepsis, n (%) 1 (20) 7 (35) 5 (25) 13 (29) Mortality, n (%) 8 (80) 9 (38) 7 (32) 24 (43) ICU stay, days, mean ± sd 20.9 ± 14.3 29.1 ± 24.2 25.8 ± 16.0 26.4 ± 19.6 Hospital stay, days, mean ± sd 22.5 ± 15.4 54.5 ± 38.1 54.3 ± 54.5 48.7 ± 43.9 SD: Standard Deviation. AB: Antibiotic APACHE: Acute Physiology and Chronic Health Evaluation. MPI: Mannheim Peritonitis Index. PRASOM: Predictor Recurrence Abdominal Sepsis Open Management. R: Resistant to initial antimicrobial treatment. CNS: Coagulase-Negative Staphylococcus. spp: Species. Table 2: Baseline characteristics according to indication for OMA in 56 patients.

54


Univariate analysis Table 3 shows the patient characteristics and selected scoring systems in relation to recurrence of abdominal sepsis and mortality on the day antibiotics were discontinued. Age above 60 years was not associated with an increased risk of recurrence of abdominal sepsis, but it did show a two-fold increase in the risk of death. None of the individual characteristics shown in table 3 had a statistically significant relationship with recurrent sepsis, except blood albumin which was associated with an almost six times higher risk of recurrence (HR 5.6; 95%CI:1.2-25.4) when depletion was below the median level of this severely ill patient group (23 g/L). The highest risk of death was observed in the pancreatitis group. Patients with organ failure or those who needed inotropic agents had five to seven-fold higher risks of death on the day antibiotics were stopped. Both higher values of the APACHE II and the PRASOM-score were associated with an increased risk for recurrence of abdominal sepsis and an increased risk of death. Within the first 24 hours of OMA (Table 4), elevated band cells were associated with an increased risk of death and patients with pancreatitis had the highest mortality risk. Age above 60 years, higher scores for PRASOM, APACHE II and the MPI showed a tendency to an increased risk of death, while a low blood albumin level was not statistically associated with higher mortality rates.

55

Chapter III

Recurrence Rate HR (95%CI) Mortality

Rate HR (95%CI)

(n=45) (n=45) Male sex, n (%) 5 (22) 0.5 (0.2-1.6) 9 (39) 2.8 (0.8-9.6) Age > 60 years, n (%) 7 (30) 1.0 (0.3-2.9) 9 (39) 2.0 (0.6-6.6) Referred, n (%) 3 (16) 0.4 (0.1-1.5) 5 (26) 1.0 (0.3-3.1) Anastomotic dehiscence, n (%) 7 (35) Ref.$ 5 (25) Ref.$ Perforation, n (%) 5 (25) 0.7 (0.2-2.3) 5 (25) 1.1 (0.3-3.7) Pancreatitis, n (%) 1 (20) 0.7 (0.1-5.3) 3 (60) 8.8 (1.8-42.5) Body temperature - <360C or >380C, n (%)

3 (33)

1.3 (0.4-4.7)

3 (33)

0.8 (0.2-2.8)

Hematocrit (% of RBC) - < 30%, n (%)

5 (29)

1.1 (0.3-3.3)

6 (35)

1.1 (0.4-3.7)

Trombocytes (x109/L) - >200, n (%)

9 (27)

0.6 (0.2-2.0)

8 (24)

0.5 (0.1-1.9)

White cell count (x109) - <4.0 or >12.0, n (%)

9 (28)

0.9 (0.3-14.3)

9 (28)

0.7 (0.2-2.4)

Segmented granulocytes (% of WCC) - <40% or >72%, n (%) 9 (30)

1.0 (0.3-3.3)

9 (30)

1.3 (0.4-4.3)

Band cells (% of WCC) - >4%, n (%)

1 (50)

1.9 (0.2-14.3)

1 (50)

3.2 (0.4-25.0)

Creatinin > 150 µmol/L, n (%) 0 0.04 (0-128.2) 3 (75) 3.3 (0.7-12.3) Albumin <23 g/L, n (%) 11 (50) 5.6 (1.2-25.4) 8 (36) 1.6 (0.5-5.0) Organ failure, n (%) 0 0.04 (0-321.1) 3 (100) 4.9 (1.3-18.4) Hypotension, n (%) 0 0.04 (0.0-100.0) 2 (50) 1.3 (0.3-6.0) Use of inotropics, n (%) 5 (46) 2.0 (0.7-6.2) 7 (64) 7.1 (2.1-24.4) APACHE II score > 10 4 (36) 1.3 (0.4-4.4) 8 (73) 4.7 (1.5-14.8) MPI > 27 - - - - PRASOM -score > 6 3 (33) 1.1 (0.3-4.0) 6 (67) 3.9 (1.3-11.8)

$ Ref.: Anastomotic dehiscence was taken as reference category. RBC: Red Bloodcell Count. WCC: White Cell Count. APACHE: Acute Physiology and Chronic Health Evaluation. MPI: Mannheim Peritonitis Index. PRASOM: Predictor Recurrence Abdominal Sepsis Open Management. Table 3: Univariate Cox regression analysis of patient characteristics at the day of discontinuation of antibiotic treatment and the risk of recurrent abdominal sepsis and death.

56


Recurrence Rate HR (95%CI) Mortality

Rate HR (95%CI)

(n=56) (n=56) Male sex, n (%) 5 (18) 0.6 (0.2-1.7) 14 (50) 1.6 (0.7-3.7) Age > 60 years, n (%) 7 (25) 1.3 (0.4-3.8) 14 (50) 1.5 (0.6-3.3) Referred, n (%) 3 (12) 0.4 (0.1-1.3) 11 (44) 1.2 (0.5-2.7) Anastomotic dehiscence, n (%) 7 (29) Ref.$ 9 (38) Ref.$ Perforation, n (%) 5 (23) 0.6 (0.2-2.0) 7 (32) 0.8 (0.3-2.2) Pancreatitis, n (%) 1 (10) 0.4 (0.1-3.6) 8 (80) 4.9 (1.8-13.5) Body temperature - <360C or >380C, n (%)

7 (19)

0.7 (0.2-2.0)

18 (50)

2.4 (0.9-6.2)

Hematocrit (% of RBC) - < 30%, n (%)

7 (37)

3.3 (1.1-9.8)

12 (63)

1.8 (0.8-4.2)

Trombocytes (x109/L) - >200, n (%)

5 (20)

0.9 (0.3-3.1)

7 (28)

0.3 (0.1-0.8)

White cell count (x109) - <4.0 or >12.0, n (%)

10 (24)

1.2 (0.3-4.3)

15 (37)

0.5 (0.2-1.3)

Segmented granulocytes (% of WCC) - <40% or >72%, n (%) 11 (24)

1.4 (0.3-6.4)

16 (35)

0.5 (0.2-1.2)

Band cells (% of WCC) - >4%, n (%)

4 (15)

0.5 (0.2-1.7)

16 (35)

2.7 (1.2-6.3)

Creatinin > 150 µmol/L, n (%) 2 (12) 0.6 (0.1-2.5) 12 (71) 2.9 (1.3-6.7) Albumin <18 g/L, n (%) 8 (27) 1.4 (0.5-4.3) 12 (40) 0.8 (0.3-1.7) Organ failure, n (%) 2 (10) 0.3 (0.1-1.4) 12 (57) 1.9 (0.9-4.3) Hypotension, n (%) 5 (15) 0.4 (0.1-1.1) 16 (48) 1.8 (0.7-4.4) Use of inotropics, n (%) 9 (19) 0.4 (0.1-1.3) 22 (47) 2.3 (0.5-9.8) APACHE II score > 10 7 (21) 0.7 (0.2-2.0) 18 (55) 2.0 (0.8- 5.1) MPI > 27 8 (20) 0.6 (0.2-1.9) 19 (48) 1.2 (0.4-3.3) PRASOM-score > 6 9 (19) 0.4 (0.1-1.2) 23 (49) 5.9 (0.8-43.6)

$ Ref.: Anastomotic dehiscence was taken as reference category. RBC: Red Bloodcell Count. WCC: White Cell Count. APACHE: Acute Physiology and Chronic Health Evaluation. MPI: Mannheim Peritonitis Index. PRASOM: Predictor Recurrence Abdominal Sepsis Open Management. Table 4: Univariate Cox regression analysis of patient characteristics at the start of OMA and the risk of recurrent abdominal sepsis and death.

57

Chapter III

Multivariate analysis Table 5 shows the results of the multivariate analysis. The single variable independently related to recurrent sepsis from the day of discontinuation of antibiotics was the blood albumin level, with levels below the median of this patient group (23 g/L) related to an increased risk for recurrence of abdominal sepsis. The ROC-curves representing the prediction on the day of antibiotic cessation of recurrence of abdominal sepsis are shown in figure 1. The areas under the curves show unsatisfactory prediction by the PRASOM-score (AUC 0.65; 95% CI:0.48-0.83) in comparison with the predicted probability calculated with the low blood albumin level (AUC 0.73; 95%CI:0.57-0.89) on the day of antibiotic cessation, but it predicted better than the APACHE-II score (AUC 0.58; 95%CI:0.41-0.76). For mortality the use of inotropics (HR 7.7; 95%CI:2.1-28.2), increased bandcells (HR 7.3; 95%CI:0.8-68) and presence of organ failure (HR 4.9; 95%CI:1.2-19.6) were the only individual statistically significant predictors that remained after multivariate analysis. The predictive model, based on band cells, organ failure and inotropic dependence, with an AUC of 0.80 (95%CI:0.63-96) was better in comparison with the prediction models of the APACHE-II score (AUC 0.78; 95%CI:0.62-0.93) and the PRASOM-score (AUC 0.75; 95%CI:0.60-0.91) (Fig.2). On the day OMA was started the predicted probability for death based on the six characteristics from our multivariate analysis show the largest AUC (0.96; 95%CI:0.90-1.00), compared with the PRASOM-score (AUC 0.75; 95%CI:0.61-0.88), APACHE-II score (AUC 0.70; 95%CI:0.56-0.85) and MPI (AUC 0.67; 95%CI:0.52-0.82).

58


Day antibiotic discontinuation

Day start OMA

Individual variables

Recurrent sepsis

HR (95%CI)

Mortality

HR (95%CI)

Recurrent sepsis

HR (95%CI)

Mortality

HR (95%CI)

Pancreatitis 22.3 (5.1-98) Temperature (0C) <36 or >38

7.6 (1.6-35)

Hematocrit < 30% RBC 4.2 (1.3-13.2) 2.9 (1.1-7.4) Trombocytes (x109/L) > 200

0.06 (0.01-0.029)

White cell count (x109) <4 or >12

0.07 (0.02-0.34)

Band cells > 4% WCC 7.3 (0.8-68) Creatinin >150 (µmol/L) 7.5 (2.2-25.6) Albumin < 23 g/L 5.6 (1.2-25.4) Hypotension Inotropic dependant 7.7 (2.1-28.2) 0.28 (0.08-0.97) Organ failure present 4.9 (1.2-19.6)

OMA: Open management of the abdomen. RBC: Red Bloodcell Count. WCC: White Cell Count. Table 5: Results of the multivariate Cox-regression analysis.

59

Chapter III

Discussion Despite improved surgical techniques, better antibiotics and advances in intensive care management, mortality rates of patients with severe secondary peritonitis remain high.1-3 Scoring systems as APACHE-II and MPI were developed to identify high-risk patients and to evaluate their prognosis.9 In addition the PRASOM-score was developed to predict recurrence of abdominal sepsis at the moment antibiotic treatment was considered to be stopped safely, but this scoring system was never validated in an external dataset.10 This study was performed to validate the PRASOM-score and to evaluate the currently existing scoring systems in patients undergoing OMA for severe secondary peritonitis. Although patients were allocated to different antibiotic treatment regimens (short or prolonged antibiotic treatment), treatment allocation did not appear to contribute to the prediction of recurrent abdominal sepsis or mortality in any of our models. In the univariate analysis both the PRASOM and the APACHE-II score were able to predict an increased risks for recurrence of abdominal sepsis and death, from the day antibiotic treatment was discontinued (Table 3). Within the first 24h of OMA, higher scores of PRASOM, APACHE-II and MPI all tended to be suggestive of an increased risk of death, as previous studies have shown.9,14,15 The limited sample size of our study may have contributed to the modest prognostic value of these scores; another explanation may be the specific selection of patients. The multivariate analysis resulted in three predictive models after Cox proportional hazards regression (Table 5). Blood albumin level, a known indicator of treatment-failure and predictor of mortality in intra-abdominal infections16,17, was the only individual predictor for recurrence of abdominal sepsis on the day antibiotic treatment was stopped and performed better than the PRASOM-score (Fig. 1). However, due to the limited number of patients in whom abdominal sepsis recurred (13), our prediction model based on blood albumin alone will hardly be satisfactory, because in clinical practice it is unrealistic to continue antibiotic treatment until albumin level is within its normal limits.

60


1 - Specificity

1,0,8,5,30,0

Sens

itivi

ty

1,0

,8

,5

,3

0,0

Reference Line

Prasom dag AB stop

Apache dag AB stop

Albumin < 23 g/L

1 - Specificity

1,0,8,5,30,0

Sens

itivi

ty

1,0

,8

,5

,3

0,0

Reference Line

Prasom dag AB stop

Apache dag AB stop

Combined modelCombined model

a APACHE: Acute Physiology and Chronic Health Evaluation. b PRASOM: Predictor Recurrence Abdominal Sepsis Open Management.

Figure 2: Receiver operating characteristic curves for risk assessment of death of the PRASOM, APACHE-II and predicted probability of the combined model includingband cells, organ failure and inotropic dependency on the day of antibiotic cessation.

Figure 1: Receiver operating characteristic curves for risk assessmentof recurrent abdominal sepsis of the PRASOM, APACHE-II andpredicted probability of blood albumin level on the day of antibioticcessation.

APACHE-II scoreb

PRASOM-scorea

Reference Line

APACHE-II scoreb

PRASOM-scorea

Reference Line

Albumin < 23 g/L

61

Chapter III

For mortality, newly formed leukocytes, organ failure and dependency on inotropic agents had predictive value. The multivariate model showed better prediction of death than the PRASOM and the APACHE-II score, according to the areas under the curves (Fig.2). These observations must be interpreted with caution, because the PRASOM-score was developed to predict recurrence of abdominal sepsis and predictions based on the APACHE-II score are often performed at the start of treatment. However, it does suggest that the other predictive variables incorporated in both PRASOM and APACHE-II score do not have added value in the prediction of death from the day antibiotics are discontinued. On the day OMA started higher scores of both APACHE-II and MPI showed an increased risk of death in the univariate analysis, but they were not superior to our prediction model calculated in the multivariate analysis. This prediction model is more solid, in comparison with the model of recurrence of abdominal sepsis on the day of antibiotic cessation, because more variables could be entered and there were more outcomes.18 In accordance with literature the source of intra-abdominal infection was one of the most important determinants of outcome.19 In our study eight of ten patients with a severe secondary peritonitis due to necrotizing pancreatitis died during OMA. In our multivariate model pancreatitis resulted in an increased risk of death in this group of patients at the start of OMA. There was no indication these patients were more severely ill according to the APACHE II scores. In conclusion, the external validation of the PRASOM-score in predicting recurrence of abdominal sepsis from the day antibiotic treatment was discontinued showed positive predictive values with higher PRASOM-scores. Predictive values of APACHE-II and MPI were also confirmed. Individual predictive variables derived from the multivariate analysis of this study showed better predictive values than the existing scoring systems, but these were derived from a small dataset and will have to be validated in a larger patient population. Nevertheless, it does mean there is room for improvement in developing prognostic scoring systems for patients with severe

62


secondary peritonitis. Perhaps a combination of variables or adding predictive values from our multivariate analysis to the PRASOM-score can in future lead to better prognostic scoring systems, which can be performed during the course of treatment and can give an indication as to when (antibiotic) treatment can be safely discontinued.

63

Chapter III

References 1. Lamme B, Boermeester MA, Reitsma B et al. Meta-analysis of

relaparotomy for secondary peritonitis. Br J Surg 2002; 89:1516-24.

2. van Goor H. Interventional management of abdominal sepsis: when and how. Langenbeck�s Arch Surg 2002; 387:191-200.

3. Mulier S, Penninckx F, Verwaest C et al. Factors affecting mortality in generalized postoperative peritonitis: multivariate analysis in 96 patients. World J Surg 2003; 27:379-84.

4. Wittmann DH, Schein M, Condon RE. Management of secondary peritonitis. Ann Surg 1996; 224:10-18.

5. Bosscha K, Hulstaert PF, Visser MR et al. Open management of the abdomen and planned reoperations in severe bacterial peritonitis. Eur J Surg 2000; 166:44-9.

6. Schein M. Surgical management of intra-abdominal infection: is there any evidence? Langenbeck�s Arch Surg 2002; 387:1-7.

7. Wacha H, Hau T, Dittmer R et al. Risk factors associated with intra-abdominal infections: a prospective multicenter study. Langenbeck�s Arch Surg 1999; 384:24-32.

8. Sotto A, Lefrant JY, Fabro-Peray P et al. Evaluation of antimicrobial therapy management of 120 consecutive patients with secondary peritonitis. JAC 2002; 50:569-76.

9. Bosscha K, Reijnders K, Hulstaert PF et al. Prognostic scoring systems to predict outcome in peritonitis and intra-abdominal sepsis. Br J Surg 1997; 84:1532-4.

10. Visser MR, Bosscha K, Olsman J et al. Predictors of recurrence of fulminant bacterial peritonitis after discontinuation of antibiotics in open management of the abdomen. Eur J Surg 1998; 164:825-9.

11. van Loon HJ, Bosscha K, Visser MR, Algra A, Verhoef J, van der Werken Chr. Short versus prolonged antibiotic treatment during open management of the abdomen. Submitted for publication.

12. Schein M. Planned reoperations and open management in critical intra-abdominal infections: prospective experience in 52 cases. World J Surg 1991; 15:537-45.

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13. Horan TC, Gaynes RP, Martone WJ et al. CDC definitions of nosocomial surgical site infections, 1992:a modification of CDC definitions of surgical wound infections. Infect Control Hosp Epidemiol 1992; 13:606-8.

14. Nystrom PO, Bax R, Dellinger EP et al. Proposed definitions for diagnosis, severity scoring, stratification, and outcome for trials on intra-abdominal infection. World J Surg 1990; 14:148-58.

15. Ohman C, Hau T. Prognostic indices in peritonitis. Hepatogastroenterology 1997; 44:937-46.

16. Christou NV, Barie PS, Dellinger EP et al. Surgical Infection Society intra-abdominal infection study: prospective evaluation of management techniques and outcome. Arch Surg 1993; 128:193-9.

17. Pacelli F, Doglietto GB, Alfieri S et al. Prognosis in intra-abdominal infections. Multivariate analysis on 604 patients. Arch Surg 1996; 131:641-5.

18. Harrel FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15:361-81.

19. Merlino JI, Malangoni MA, Smith CM et al. Prospective randomized trials affect the outcomes of intra-abdominal infection. Ann Surg 2001; 6:859-66.

65

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66

Chapter IV

Antibiotic Rotation and Development of Gram-Negative Resistance in ICU.

The Cyclone trial

H.J. van Loon, M.R. Vriens, A.C. Fluit, A. Troelstra, Chr. van der Werken, J. Verhoef and M.J.M. Bonten

Accepted for publication

American Journal of Respiratory Critical Care Medicine in press

Chapter IV

Abstract To attain a better understanding of antibiotic cycling and its effects on the epidemiology of antibiotic resistance in Gram-negative microorganisms, two different antibiotic classes (quinolone and beta-lactam) were cycled during four 4-month periods in a surgical ICU. Respiratory aspirates and rectal swabs were obtained and DNA-fingerprinting was performed. Primary endpoint of the study was the acquisition rate with Gram-negative bacteria resistant to the antibiotic of choice during each cycle. Secondary endpoints were changes in endemic prevalence of resistant bacteria and the relative importance of cross-transmission. In all, 388 patients were included and 2520 cultures analyzed. Adherence to antibiotic protocol was 96%. Overall antibiotic use increased with 24%. Acquisition rates with resistant bacteria were highest during levofloxacin exposure (RR 3.2; 95%CI:1.4-7.1) and piperacillin/tazobactam exposure (RR 2.4; 95% CI 1.2-4.8). The relative importance of cross-transmission decreased during the study. For individual patients treatment with levofloxacin was the only independent risk factor for acquisition of levofloxacin-resistant bacteria (HR 12.6; 95% CI 3.8-41.6). Potential for selection of antibiotic-resistant Gram-negative bacteria during periods of homogeneous exposure increased from cefpirome to piperacillin/tazobactam to levofloxacin. Cycling of homogeneous antibiotic exposure is unlikely to control the emergence of Gram-negative antimicrobial resistance in ICUs.

68

Antibiotic Rotation and Gram-Negative Resistance

Introduction The increase in multi-resistant microorganisms, both Gram-positive and Gram-negative, is an alarming problem world-wide, especially for intensive care unit (ICU) patients.1,2 This global emergence of antibiotic resistance is fueled by the widespread use of broad-spectrum antibiotics, creating a continuous selective pressure, and by lapses in infection control, that facilitate transmission of resistant pathogens. Dynamics of antibiotic resistance within hospital settings are determined by introduction of resistance, cross-transmission, and selection and induction of resistant strains during antibiotic therapy3. Multiple strategies have been designed to limit or reverse the emergence of antibiotic resistance, such as, improving infection control measures4-6 and reducing unnecessary and inappropriate antibiotic use7,8. In addition, rotation or cycling of antimicrobial agents has been proposed as a strategy to limit the selective pressure of specific antibiotic classes, by periodically changing standard antibiotic regimens in patient populations. However, these studies either had a non-structured cycling scheme9, only evaluated changes in empirical therapy10, used multiple antibiotics for cycling and had different cycling periods9,11, were difficult to interpret because of concomitant reductions in overall antibiotic use12, or changes in infection control strategies13. In none of these studies all aspects of the dynamics of antibiotic resistance within small hospital settings (i.e., relative importance of introduction, cross-transmission and selection) were addressed, precluding a reliable estimation of the potential efficacy of antibiotic cycling. Furthermore, the optimal antibiotic choices and duration of cycle periods remain unknown14,15. In order to attain a better understanding on the epidemiology of antibiotic resistance in Gram-negative microorganisms, we performed a prospective study in which two different antibiotic classes (quinolones and beta-lactam antibiotics), with different mechanisms for resistance development were cycled during four 4-month periods in a surgical ICU. Colonization with antibiotic-resistant Gram-

69

Chapter IV

negative bacteria was determined with intensive surveillance and bacterial genotyping was used to identify different acquisition routes. Materials and Methods Setting and study population The study was performed between February 2001 and June 2002 in the 8 bed surgical ICU (SICU) of the University Medical Center Utrecht (UMCU) in The Netherlands. The SICU consists of three separate single bedrooms, each with an anteroom and a center room with 5 beds. Patients were excluded from the protocol if they had a history of allergy to one of the study drugs, had meningitis or a brain abscess and if they were expected to be admitted to the SICU for less than 24 hours. No surveillance cultures were obtained from the excluded patients. The study was approved by the Medical Ethical Committee of the UMCU that waived the need for informed consent, considering the observational nature of the study, the use of conventional antibiotic therapy, the routine performance of surveillance cultures and the maintenance of optimal patient care. Study design The 16-month study consisted of four 4-month periods with cycling antibiotic policies. During cycles I and III, use of beta-lactam antibiotics was avoided and levofloxacin 500 mg intravenously once daily was the empiric antibiotic of choice (Table 1). During cycles II and IV quinolones were avoided and beta-lactam antibiotics served as treatment of choice; cefpirome 2 grams intravenously twice daily in cycle II and piperacillin/tazobactam 4.5 gram intravenously thrice daily in cycle IV. Deviation from protocol was allowed only if patients were known to be colonized with microorganisms resistant to the antibiotic of choice during that specific cycle, or if they had medical contraindications for these agents.

70


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71

Chapter IV

Infections caused by Gram-negative bacteria resistant for levofloxacin were treated with trimethoprim-sulfamethoxazole (TMP-SMX) or meropenem (in case of TMP-SMX resistance). Instituted antimicrobial therapy was regarded as definitive treatment and not changed upon susceptibility results or when study periods changed. Non-compliance to protocol was expressed as the number of antibiotic courses not in accordance with the empiric antibiotic strategy during that specific cycle. Infection control measures All standard infection control procedures, as used in our hospital, were maintained. These include strict isolation of patients colonized with methicillin-resistant S. aureus (MRSA). In case of colonization (or infection) with aminoglycoside-resistant Gram-negative bacteria active surveillance among other patients and barrier precautions (i.e., the use of gowns and gloves during patient-contact by nursing and medical staff) for those found to be colonized were implemented. After four weeks of study in cycle I, when resistance to levofloxacin emerged, it was decided that barrier precautions were also implemented for patients colonized with Gram-negative bacteria resistant to any of the three rotation antibiotics. All analyses were performed for the whole study period and for the whole study period minus these four weeks, in order to control for this change in infection control policy. Only overall results are presented, as they appeared not to be influenced by excluding the initial four weeks. Microbiological investigations Respiratory aspirates and rectal swabs were taken from all patients upon admission to the SICU, thereafter once a week and on discharge from the ICU and processed according to standard methods. Morphologically different Gram-negative colonies were selected for further identification and susceptibility testing using the Vitek I system (bioMérieux, France). Additional susceptibility tests for

72


levofloxacin and cefpirome were performed by means of the disk-diffusion method, according to the National Committee for Clinical Laboratory Standards (NCCLS).16 Gram-negative isolates were typed using the automated RiboPrinter Microbial Characterization System (Qualicon Europe Ltd., Warwick, United Kingdom) as described earlier.17 Data collection Clinical data were collected on patients’ demographics, diagnosis, the Acute Physiology and Clinical Health Evaluation score (APACHE-II score) on admission, complications, duration of ICU stay and mortality. All antibiotics prescribed were recorded, including the duration and dose. Primary outcomes The primary outcome measure was the acquisition rate of Gram-negative bacteria resistant to the antibiotic of choice during each cycle. Secondary endpoints included mean point prevalence of colonization with Gram-negative microorganisms in each cycle, antibiotic use, relative importance of endogenous and exogenous colonization and patient-specific risk factors for colonization with resistant microorganisms. Definitions Colonization on admission was defined as a positive culture with Gram-negative microorganisms within 48h of admission to the SICU. Acquired colonization was defined as a positive culture after 48h of admission with previous negative culture results. Acquisition rates were expressed as the total number of patients with acquired colonization divided by the total number of patientdays at risk (i.e., the number of colonization-free days from ICU admission until colonization with the microorganism of interest. Thus, for individual

73

Chapter IV

patients number of days at risk may vary per antibiotic. Acquisition rates were expressed per 1000 patientdays at risk. Daily prevalences of resistance were defined as the number of patients colonized with a Gram-negative microorganism resistant to an antibiotic divided by the total number of patients in the ward on that day. Once a patient was colonized with an antibiotic-resistant microorganism, he/she was considered colonized until discharge. Colonization pressure was expressed as the mean of the daily prevalences for a period of time. Acquired colonization could be from endogenous or exogenous origin. Exogenous colonization was defined as acquired colonization with a microorganism with an antibiotic resistance profile and genotype identical to that of a microorganism, belonging to the same species, and isolated previously from another patient present in an overlapping time-frame in the ward. Endogenous colonization was defined as acquired colonization with a microorganism with an unique genotype. As patients can acquire colonization with more than one microorganism, both routes of colonization could be demonstrated in individual patients. Antibiotic usage was expressed in defined daily dosage (DDD) per 1000 patientdays. In risk factor analysis, exposure to a certain antibiotic for an individual patient was expressed as the number of DDDs divided by the days at risk for acquiring colonization. Statistical analysis Risk factors for acquisition of resistant Gram-negative bacteria were determined in univariant and multivariant analyses. Because of the relevance of duration at risk in univariate analysis, a Cox proportional hazard model was used for multivariate analysis. Independent samples t-test, chi-square test and Mann-Whitney U test were used when appropriate. Statistical significance was considered for P-values less than 0.05.

74


Results Patients During the period of study 388 patients were admitted to the surgical ICU, of whom 38 were discharged within the first 24 hours and nine died on the day of admission. Thus, 341 patients were included, representing 358 admissions (15 patients admitted twice and one patient thrice) (table 2). Demographic characteristics and outcome data, such as mortality rates and length of stay, were comparable for the four cycles. Antibiotic use In 95.6% of all cases antibiotics were prescribed according to protocol, varying from 88.5% in cycle I upto 100% in cycle II. Proportions of quinolone use were 27% and 31% in cycles I and III and 0% and 3% in cycles II and IV (Table 3). In contrast, proportions of beta-lactam use were 39% and 49% in cycles II and IV and 9% and 1.5% in cycles I and III. Overall antibiotic use increased with 24% during the 16-month study period; from 816 DDD/1000 patientdays in cycle I to 1009 DDD/1000 patientdays in cycle IV. The increase was apparent for several groups of antibiotics. As compared to cycle I the use of the three protocolized antibiotics increased with 74% in cycle IV, carbapenem use increased with 159.5% in cycle III and with 69.5% in cycle IV and aminoglycoside use increased with 110% in cycle IV. The number of patients receiving any of the protocolized antibiotics (Table 4) remained stable throughout the four cycles (range 37-54 per cycle), with the lowest number of patients in cycle IV. The mean duration of therapy increased from 5.4 ± 3.7 days in cycle I to 10.8 ± 13.4 days in cycle IV (P=0.014). Similarly, numbers of patients receiving carbapenems per cycle did not change dramatically (range from 9-17 patients), but duration of therapy increased from 5.6 ± 4.3 days in cycle I to 10.2 ± 9.5 and 10.5 ± 7.4 days in cycles III (P=ns) and IV (P=ns), respectively.

75

Chapter IV

Cycle I Cycle II Cycle III Cycle IV

Days 120 122 122 121 Patients present at start of the cycle 8 5 7 6 Admissions 89 106 96 59 Admissions/day 0.74 0.87 0.79 0.49 Patient days 946 942 947 958 Male, n (%) 62 (63.9) 69 (65.0) 54 (56.3) 45 (76.3) Mean age, years ± sd 55.6 ± 17.6 59.9 ± 18.5 55.6 ± 18.6 59.0 ± 16.2 Medical history Cardiovascular 42.3% 43.4% 37.5% 44.1% Respiratory 20.6% 20.8% 12.5% 13.6% Gastrointestinal 44.3% 39.6% 27.1% 32.2% Urogenital 28.9% 27.4% 24.0% 20.3% Neurological 21.6% 18.9% 13.5% 11.9% Endocrinological 18.6% 15.1% 10.4% 13.6% Reason for ICU admittance Surgery 62.9% 63.2% 70.8% 74.6% Sepsis 16.5% 19.8% 12.5% 8.5% Respiratory insufficiency 19.6% 17.0% 14.6% 16.9% Poly-trauma 1.0% 0.0% 2.1% 0.0% APACHE-II score, median (IQR) 11 (8-15) 12.0 (8-15) 11.5 (8.0-15.3) 13.0 (7.5-17.0) Mean duration of stay, days ± sd 11.0 ± 20.7 8.06 ± 13.12 10.92 ± 21.58 14.39 ± 26.85 Median duration of stay, days (IQR) 3.0 (1-11) 3 (1-8) 3 (1-8.6) 4 (1-20)

Mortality, n (%) 11 (11.3) 10 (9.4) 14 (14.6) 12 (20.3) Sd: standard deviation IQR: Interquartile Range No statistically significant differences in between cycles.

Table 2: Baseline patient characteristics.

76


For patients receiving aminoglycosides (range 12-20 per cycle) duration of therapy increased from 7.1 ± 5.8 days in cycle I to 16.1 ±14.3 days in cycle IV (P=0.027). Mean duration of aminoglycoside use during cycle IV, when including all patients, was 3.4 ± 8.0 (0-32 days). In fact, the longer durations of antibiotic therapy were caused by multiple episodes of short courses (all antibiotic courses,in days, summed per patient), while the duration of each individual episode remained stable (data not shown).

DDD/1000 ptn days Cycle I Cycle II Cycle III Cycle IV Quinolone 220.9 0.0* 305.2* 28.2* Cefpirome 0.0 306.8 0.0 0.0 Pip/Taz 19.0 8.5 1.1 390.4* Protocolized antibiotics 240.0 315.3 306.2 418.6 Other beta-lactam 57.1 13.8 13.7 101.3#

Carbapenem 70.8 104.0 183.7 120.0 Aminoglycoside 120.5 136.9 136.2 252.6# Vancomycin 62.4 65.8 136.2 62.6 Clindamycin 136.4 59.4# 61.2 21.9 Metronidazole 107.8 156.1 154.2 8.4# TMP-SMX 21.1 0.0 4.2 24.0 Total DDD/1000 ptn days$ 816.1 851.4 995.8 1009.4 Proportion quinolone 27.1% 0.0% 30.6% 2.8% Proportion beta-lactam 9.3% 38.7% 1.5% 48.7%

Protocolized antibiotics: The sum of DDDs of quinolons, cefpirome and piperacillin/tazobactam. Other Beta-lactams: The sum of DDDs of all beta-lactams other than cefpirome and piperacillin/tazobactam. Carbapenems: The sum of DDDs of meropenem and imipenem. Aminoglycosides: The sum of DDDs of gentamycin, tobramycin and amikacin. TMP-SMX: trimethoprim-sulfamethoxazole. $ The protocolized antibiotics were included only once. * P <0.001 compared to previous cycle. # 0.05 > P ≤ 0.001 compared to previous cycle.

Table 3: Antibiotic use in Daily Defined Dosage per 1000 patientdays.

77

Chapter IV

Proportion Ptn Cycle I Cycle II Cycle III Cycle IV Quinolone 0.40(39) 0.00* 0.52(54) * 0.05(3) * Cefpirome 0.00 0.44(49) * 0.00* 0.00 Pip/Taz 0.06(6) 0.01(1) 0.01(1) 0.55(36) * Protocolized AB 0.43(42) 0.45(50) 0.52(54) 0.57(37) Other beta-lactam 0.11(11) 0.05(5) 0.06(6) 0.11(7) Carbapenem 0.12(12) 0.08(9) 0.17(17) 0.17(11) Aminoglycoside 0.17(16) 0.18(20) 0.12(12) 0.23(15) Vancomycin 0.13(13) 0.10(11) 0.16(16) 0.08(5) Clindamycin 0.21(20) 0.12(13) 0.11(11) 0.03(2) Metronidazole 0.17(16) 0.26(29) 0.27(28) 0.02(1) * TMP-SMX 0.03(3) 0.00 0.01(1) 0.06(4)

TMP-SMX: trimethoprim-sulfamethoxazole. * P <0.001 compared to previous cycle.

Table 4: The proportion of patients that received the specific antibiotics. Microbiological results. In all, 2520 surveillance cultures were obtained (1262 tracheal aspirates and 1258 rectal swabs) representing a mean of 5.9 cultures per patient (range 1 to 136) and yielding 3819 microorganisms. Percentages of patients colonized per cycle ranged from 71% to 77% (P=ns) for Enterobacteriaceae, from 17% to 30% (P=ns) for Pseudomonas aeruginosa (P=ns) and from 5% to 16% (P=0.02) for other non-fermenters. Rates of patients colonized with resistant Gram-negative microorganisms on admission were low (range 0 to 4 patients per cycle) and did not change in between cycles (Table 5). Mean colonization pressure per month for levofloxacin resistance was highest (0.52) in month 3 (cycle I), dropped to zero in month 9 (start of cycle III) and then increased to 0.37 in months 14 and 15 (Cycle IV) (Figure 1).

78


0,00

0,10

0,20

0,30

0,40

0,50

0,60

feb-01

mrt-01

apr-01

mei-01

jun-01

jul-01

aug-01

sep-01

okt-01

nov-01

dec-01

jan-02

feb-02

mrt-02

apr-02

mei-02

month

mea

n co

lloni

zatio

n pr

essu

re

Levo_RCfp_RPtz_R

Figure 1: Average monthly prevalence of colonization with resistant Gram-negative microorganisms for levofloxacin (Levo_R), cefpirome (Cfp_R) and piperacillin/tazobactam (Ptz_R). In contrast, mean colonization pressure per month for cefpirome resistance was low (<0.1) during cycle I but increased in month 6 (cycle II) to 0.30, decreased to zero in month 11 and then increased to 0.51 in month 16 (cycle IV). Mean colonization pressure per month for piperacillin-tazobactam resistance was generally low during cycles I-III with a peak of 0.25 in month 6 (cycle II), but increased to 0.33 in month 14 (cycle IV) and finally decreased to 0.15 in the remaining 2 months. Monthly acquisition rates clearly peaked for levofloxacin resistance in month 3 (cycle I) and months 11 and 12 at the end of cycle III (Figure 2). Acquisition rates for Gram-negative bacteria resistant for levofloxacin were 23.1 and 16.8/1000 days at risk in cycle I and III, as compared to 5.3 and 5.0/ 1000 days at risk in cycles II and IV. Overall, acquisition rates for levofloxacin resistance were 19.6/1000 days at risk during periods of exposure (cycles I and III) and 5.2/1000 days at risk in periods of non-exposure (RR 3.2 95% CI:1.4-7.1, p=0.003).

79

Chapter IV

Cycle I Cycle II Cycle III Cycle IV

No. of patients colonized with GNR on Levo 4 0 1 3 admission resistant for: Cfp 2 0 3 2

Ptz 3 1 1 0 Total 5 1 3 5

Acq. Rate/ 1000 patient days at risk (n) Levo R 23.1 (13) 5.3 (4) 16.8 (12) 5.0 (3)

Cfp R 13.1 (10) 14.8 (10) 11.1 (9) 16.8 (9) Ptz R 7.8 (6) 11.1 (8) 8.4 (7) 16.3 (10) Total 29.6 (16) 16.8 (12) 37.9 (20) 19.5 (10)

No. of patients colonized with GNR Levo R alone 9 3 6 2 resistant to any of the study antibiotics Cfp R alone 3 2 5 1

Ptz R alone 1 1 4 2 Levo+Cfp R 2 0 3 2 Levo+Ptz R 1 0 0 0

Cfp+Ptz R 2 4 1 5 Levo+Cfp+Ptz R 5 4 4 3

Source of acquisition, n Endogenous, n 10 6 12 11

Exogenous, n 12 8 6 2

Source of specific antibiotic resistance, n endogenous Levo R 5 2 10 3

Cfp R 6 7 8 6 Ptz R 5 3 6 9

Exogenous Levo R 10 3 2 1

Cfp R 7 7 6 3 Ptz R 3 7 5 3

GNR: Gram-negative rods Levo (levofloxacin), Cfp (cefpirome), Ptz (piperacillin/tazobactam) R : resistance Table 5: Resistance determinants

80


Acquisition of cefpirome-resistant Gram-negative bacteria was highest in month 6 of the study (cycle II), but slightly lower acquisition rates were found in periods of non-exposure. Overall, acquisition rates of cefpirome-resistant Gram-negative bacteria per cycle did not differ significantly (11.1-16.8/1000 patientdays at risk). The acquisition rate for cefpirome-resistant microorganisms was 14.8/1000 days at risk during exposure (cycle II) and 13.3/1000 days at risk during periods of non-exposure (RR 0.9; 95% CI:0.4-1.7, p=0.85). Acquisition rates of piperacillin/tazobactam-resistant Gram-negative bacteria were highest during the beta-lactam cycles, with the highest acquisition rates during cycle IV (16.3/1000 days at risk) (Figure 2).

0,00

10,00

20,00

30,00

40,00

50,00

60,00

70,00

80,00

90,00

feb-01

mrt-01

apr-01

mei-01

jun-01

jul-01

aug-01

sep-01

okt-01

nov-01

dec-01

jan-02

feb-02

mrt-02

apr-02

mei-02

month

acqu

isiti

on ra

te/1

000

nega

tive

days

Levo_RCfp_RPtz_R

Figure 2: Acquisition rate of colonization with antibiotic-resistant Gram-negative

species per 1000 negative patient days each month during the study period, for levofloxacin (Levo_R), cefpirome (Cfp_R) and piperacillin/tazobactam (Ptz_R).

81

Chapter IV

In the periods of non-exposure, the overall acquistion rate for piperacillin/tazobactam was 9.0/1000 days at risk (ranging form 7.8-11.1/1000 days at risk), which was lower than during exposure (RR 2.4; 95% CI:1.2-4.8, p=0.02). Acquisition rates for any of the three protocolized antibiotics tended to be higher during cycle I and III (29.6 and 37.9/1000 days at risk) than during cycle II and IV (16.8 and 19.5/1000 days at risk) (RR 1.4; 95% CI: 0.9-2.3, p=0.20). Exogenous acquisition steadily decreased from 12 episodes in cycle I (all P. aeruginosa), to 8 episodes in cycle II (all P. aeruginosa), to three episodes in cycle III and IV (2 Enterobacteriaceae and 2 non-fermenters in cycle III and only Enterobacteriaceae in cycle IV). Figure 3 illustrates the typing results of the P.auruginosa isolates cultured during the different cycles. In contrast, occurrence of endogenous colonization remained more or less stable (ranging from 6 episodes in cycle II to 12 in cycle III) with almost equal distribution of species (15 P. aeruginosa, 19 Enterobacteriaceae and 17 non-fermenters). Endogenous and exogenous colonization were equally important during cycles I and II, with 16 and 20 cases each, whereas the endogenous route was more important during the last two cycles with 23 as opposed to 9 cases for the exogenous route (P=0.014).

82


83

Cycle I Cycle II

Cycle III Cycle IV

Figure 3: Dendrogram containing the genotyping results of different P. aeruginosa isolates during the different cycles. Only one isolate per patient was included. The “H”numbers represent the isolate number. The numbers in the second row represent the strain number, assigned after comparison with the local P. aeruginosa database.The underlined numbers represent P. aeruginosa isolates coresistant to quinolones, cefpirome and/or pip- tazo.

Chapter IV

DD

D TM

P-SMX

, mean ± sd

DD

D M

etronidazole , mean ±sd

DD

D C

lindamycin, m

ean ± sd

DD

D A

minoglycosides, m

ean ± sd

DD

D V

ancomycin, m

ean ± sd

DD

D C

arbapenem, m

ean ± sd

DD

D B

eta-lactam Total, m

ean ± sd

DD

D Pi p/Tazo, m

ean ± sd

DD

D C

efpirome, m

ean ± sd

DD

D Levofloxacin, m

ean ± sd

DD

D Q

uinolones, mean ± sd

Patientdays at risk, mean ± sd

Collonization pressure, m

ean ± sd

Cycle w

ith specific pressure, n (%)

Apache-II score, m

ean ± sd

Sex, male, n (%

)

Age, m

ean ± sd

Risk factors

0.41 ± 1.56

3.00 ± 4.75

1.56± 3.95

2.72 ± 6.49

1.47± 2.89

2.81 ± 7.20

2.38 ± 4.01

0.84 ± 2.71

1.03 ± 3.06

4.16 ± 4.40

4.16± 4.40

16.44 ± 13.1

0.23 ± 0.13

25 (78.1)

16.91 ± 6.58

17 (53.1)

52.20 ± 19.8

n=32

Levo-R

0.05 ± 5.98

0.98 ± 2.86

0.52 ± 1.98

1.29 ± 4.63

0.63 ± 2.29

0.95 ± 3.74

2.32 ± 6.10

1.01 ± 3.90

0.91 ± 2.70

0.90 ± 2.40

1.01 ± 2.60

6.69 ± 10.80

0.22 ± 0.13

165 (50.6)

11.62 ± 5.5

212 (65.0)

57.90 ± 17.7

n=326

non-Levo-R

<0.02

0.01

<0.01

0.20

0.02

0.01

0.92

0.70

0.77

<0.01

<0.01

<0.01

0.69

<0.01

<0.01

0.18

0.076

P

0.74 ± 3.17

2.34 ± 3.86

2.08 ± 3.77

3.53± 5.00

1.74 ± 3.70

3.21 ± 6.17

7.11 ± 12.06

2.89 ± 6.90

2.37 ± 4.38

3.16 ± 3.88

3.63 ± 4.31

20.89 ± 14.8

0.15 ± 0.14

10 (26.3)

15.34 ± 5.17

26 (68.4)

51.59 ± 19.91

n=38

Cfp-R

0.10 ± 1.01

1.08 ± 3.02

0.60 ± 2.12

0.86 ± 3.48

0.70 ± 2.42

0.64 ± 3.02

1.67 ± 3.80

0.72 ± 2.72

0.73 ± 2.30

1.13 ± 2.59

1.23 ± 2.76

6.39 ± 10.78

0.15 ± 0.16

94 (29.4)

11.71 ± 5.76

203 (63.4)

58.10 ± 17.6

n=320

non-Cfp-R

0.05

0.01

<0.01

<0.01

<0.01

<0.01

<0.01

0.07

0.01

<0.01

<0.01

<0.01

0.99

0.43

<0.01

0.34

0.03

P

0.90 ± 3.50

2.26 ± 4.12

2.35 ± 4.14

4.58 ± 5.21

1.65 ± 3.33

3.19 ± 6.05

6.65 ± 6.96

3.39 ± 6.47

2.48 ± 4.52

2.97 ± 4.01

3.42 ± 4.59

21.87 ± 16.1

0.10 ± 0.09

10 (32.3)

15.64 ± 4.73

19 (61.3)

50.51 ± 17.6

n=31

Ptz-R

0.13 ± 1.11

1.11 ± 3.05

0.65 ± 2.21

0.87 ± 3.58

0.70 ± 2.45

0.78 ± 3.33

1.78 ± 5.40

0.70 ± 3.07

0.77 ± 2.41

1.18 ± 2.81

1.28 ± 2.96

6.96 ± 11.43

0.09 ± 0.01

50 (15.3)

11.71 ± 5.78

209 (63.9)

58.06 ± 17.9

n=327

non-Ptz-R

0.04

0.04

<0.01

<0.01

0.01

<0.01

<0.01

<0.01

0.03

0.01

0.01

<0.01

0.34

0.02

<0.01

0.44

0.03

P

TMP-SM

X: Trim

ethoprim-sulfam

ethoxazole

Table 6: Dem

ographic and clinical characteristics of the patients by acquisition status.

84


Risk factors for colonization Acquisition of levofloxacin resistance was associated with higher APACHE II scores, being treated in ICU during cycle I or III (levofloxacin cycles), prolonged duration at risk, an increased exposure to levofloxacin, clindamycin, metronidazole and trimethorpim-sulfamethoxazole (Table 5). In multivariate Cox regression, the proportional hazard (HR) of being treated in ICU during cycles I and III for acquisition of levofloxacin-resistant Gram-negative bacteria was 12.6 (95%CI:3.8-41.6, p<0.0001). The numbers of days treated with antibiotics did not impact the risk for acquisition of levofloxacin-resistant microorganisms. Acquisition of cefpirome-resistant and piperacillin/tazobactam-resistant Gram-negative bacteria was associated with higher APACHE II scores, longer duration at risk and higher exposure to all of the antibiotics (except piperacillin/tazobactam for cefpirome-resistant bacteria), and with treatment in a period of high exposure to piperacillin/tazobactam. In multivariate Cox regression, however, none of these risk factors were significantly associated with acquisition of resistant Gram-negative bacteria. Discussion The main features of this study are (a) that, despite 96% compliance with protocol, cycling with quinolones and beta-lactam antibiotics only modified 27% to 49% of the overall antibiotic use, that (b) the use of both quinolones and piperacillin-tazobactam were associated with increased acquisition of resistance, and that (c) total antibiotic use increased with 24% during the period of the study. These findings demonstrate that cycling of homogeneous antibiotic exposure (i.e., repeated rotation of two antibiotic classes) is associated with changing profiles of resistance development, which questions its use as a strategy to prevent antibiotic resistance in ICUs. Only few studies tested the concept of cycling antibiotic classes. The hypothesis behind this strategy is that the cyclic exposure to homogeneous selective antibiotic pressure prevents emergence of

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Chapter IV

resistance in two ways. First, it is assumed that antibiotic-resistant microorganisms have a growth disadvantage when the selective antibiotic pressure is withdrawn. Therefore, resistance development during exposure will be counterbalanced during periods of non-exposure. Secondly, if resistance develops during one period, exposure to another class of antibiotics in the following cycle will eliminate the resistant microorganisms. For this to occur, mechanisms of resistance development for the different antibiotics should not be identical and cross-resistance should be absent. However, apart from theoretical considerations, many aspects of daily clinical practice may interfere with these concepts. For example, changes in the numbers of patients introducing resistant microorganisms into the unit or changes in compliance with hygienic measures will affect emergence of antibiotic resistance. The effectiveness of infection control programs can be influenced by changes in workload of health care workers or understaffing, which both will lead to more patient health care worker contacts and less adherence to hand hygiene, and thus to more transmission of pathogens.18-21 Whether the theoretically benefits of antibiotic cycling hold true in daily practice can only be tested by controlling confounding variables as much as possible. The present study shows some differences between theoretical considerations and daily clinical practice. Although resistance development against beta-lactam and fluoroquinolone antibiotics is based on different mechanisms, homogeneous exposure to one of these classes did not prevent resistance development to the other class. In addition, withdrawal of exposure was not followed by a rapid decrease of resistance, as predicted by a theoretical model.23 The absence of such a rapid decrease in resistance was at least partly due to cross-resistance to multiple antibiotics. As a result selective pressure will not decrease with a new cycle. The emerging problem of multiple resistance among Gram-negative bacteria, therefore, may well decrease the potential benefits of antibiotic cycling. Recent findings have shown that resistance to quinolones in the United States is increasing rapidly, paralleling the increased use of these agents, and that these mostly Gram-negative pathogens frequently are cross-resistant to other antibiotic classes.22 Therefore, the assumed cost of

86


resistance or eradication through exposure to a new class of antibiotics are unlikely to decrease resistance rates in such settings. As most patients remain colonized until the end of their stay in ICU, patient turnover will be the major determinant for a decrease of resistance rates (by replacing colonized by non-colonized patients), as earlier suggested by Lipsitch and coworkers.23 This is extremely important for ICU-populations that are typically small (6-15 beds), as a few outliers can maintain resistance for prolonged periods of time, even into a following period with renewed exposure to the same antibiotics. Therefore, from a theoretical point of view, rotation periods should be long enough to prevent that patients are repeatedly exposed to the same antibiotic pressure. As none of the patients in our study were treated during three consecutive periods, the four-month rotation period fulfilled to this theoretical prerequisite. Homogeneous exposure to quinolones was associated with the highest risks of acquisition of resistance, and its use appeared to be an independent risk factor for acquisition for individual patients. Homogeneous exposure to piperacillin-tazobactam was also associated with increased acquisition of resistance, though its use was not independently associated with acquisition. Based on the acquisition rates during the individual cycles and the multivariate risk factor analysis the three antibiotics could be ranked in order of increasing resistance potential from cefpirome, to piperacillin-tazobactam, to levofloxacin. Resistance to quinolone antibitotics is almost always chromosomally mediated, and therefore assumed to be extremely susceptible to inducible resistance in settings with high selective quinolone pressure. Mutations may lead to reduced cell wall permeability or upregulation of efflux pumps, with cross-resistance to carbapenems.24 In addition, exposure to fluoroquinolones was a risk factor for infection with piperacillin-tazobactam-resistant pathogens in one study.25 The inclusion of levofloxacin in two study periods may have introduced a bias against the quinolones as there is circumstantial evidence from in vitro studies and clinical observations that levofloxacin has a higher potential for resistance mutations than ciprofloxacin.26 Resistance to beta-lactam antibiotics is often plasmid mediated (although

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chromosomally mediated resistance also exists), allowing horizontal transfer of resistance genes. Naturally, all microorganisms can spread through cross-transmission. In our setting, acquired colonization with fluoroquinolone-resistant pathogens resulted mostly from cross-transmission especially during cycle I, whereas acquired colonization with beta-lactam-resistant pathogens was considered to have equally originated from endogenous and exogenous sources; either by selection of pre-existing resistant flora or through mutations. The high acquisition rate of fluoroquinolone resistance in cycle I partly resulted from exogenous acquisition of P. aeruginosa, suggesting lapses in infection control practices. Adherence to infection control measures is an important confounder in studies evaluating interventions aiming to modulate antibiotic resistance levels in ICUs. In the present study, implemented infection control measures were enforced after the first isolation of fluoroquinolone-resistant microorganisms, but remained identical for the remainder of the study. Inclusion of the first period of less stringent infection control (4 weeks) could, therefore, have led to overestimation of true effects of quinolone-exposure. Therefore, all analyses of cycle I were performed for the total cycle (16 weeks) as well as for the cycle-period after infection control measures had changed (12 weeks) (data not shown). All but one of the acquisitions, however, occurred after barrier precautions had been enforced. Restriction of the analysis to the 12-week period would have resulted in a higher acquistion rate. Therefore, we don’t feel that the implemented changes strongly affected our findings. Nevertheless, the proportion of acquisitions due to cross-transmssion steadily decreased during the period of study. As we did not monitor compliance with infection control measures we cannot exclude the possibility that growing awareness of the study among health care workers influenced their behavior, leading to lower incidences of . cross-transmission during the period of study. During the 16-month study period antibiotic use gradually increased from 816 to 1009 DDD/1000 patients days. There were no changes in patient populations that could explain this increased prescription, and as criteria for infections were not registered, we can neither confirm nor exclude that physicians had lowered their level of suspicion for

88


infection. It is possible that a (non-significant) longer ICU-stay during period 4 increased the risk for acquisition of resistant bacteria, thereby increasing the need for more and prolonged courses of antibiotics. However, total acquisition rates with resistant Gram-negative bacteria were not higher during period 4. Another possibility would be that, because of strictly protocolized antibiotic use, interaction between ICU-physicians and consulting infectious disease specialists and medical microbiologists had decreased. Several studies have shown that infectious disease consultation reduces antibiotic use.12,27,28 Monitoring of antibiotic use was continued during the first 4 months after the study had been discontinued. In this period antibiotic interaction between medical microbiologists and infectious disease specialist with intensivists re-intensified and overall antibiotic use decreased to 859 DDD/1000 patient days (data not shown). Although compliance to protocol was high (96%), proportions of protocolized antibiotics per period varied between 27% and 49%. Of note, our study was designed to rotate antibiotics for treatment of Gram-negative microorganisms only, and not for the treatment of Gram-positive or anaerobic microorganisms as antibiotic-resistance among these microorganisms is not a problem in our hospital. During the period of study there was only one patient admitted with MRSA (without spread to others) and zero patients with VRE. Antibiotic rotation had no effects on the susceptibilities of clinical isolates of S.aureus (n=115 patients) (data not shown). Moreover, use of aminoglycosides, though allowed by protocol, was not included in these proportions. With restriction to treatment of Gram-negative microorganisms and inclusion of aminoglycosides as protocolized proportional shifts per cycle would vary from 69% to 79%. However, from an ecological perspective only total antibiotic use in the unit is relevant. Our findings clearly demonstrate that even with high compliance rates, it will be difficult to create large periodic shifts in antibiotic exposure. The results of the present study identify some circumstances in which cycling of antibiotics could stimulate, rather than reduce emergence of antibiotic resistance. Assuming that introduction of resistance into the unit does not change and environmental sources can be neglected, a

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Chapter IV

period of homogeneous antibiotic exposure may lead to a higher colonization pressure, which will increase the risk of cross-transmission29, which will further increase colonization pressure. In contrast, short cycles of homogeneous antibiotic exposure, or no cycling at all, are less likely to lead to an increased colonization pressure of a certain resistance profile. Nevertheless, with poor infection control compliance, risk of cross-transmission will be the same, but will remain rather unnoticed as different resistance profiles exist. Our findings do not lend support to the concept that cycling of homogeneous antibiotic exposure will control emerging antibiotic resistance among Gram-negative microorganisms in ICUs. The classes tested in the present study both stimulated development and spread of resistance within short periods of time and cross-resistance prevented that replacement of exposure eradicated existing resistance. Moreover, overall antibiotic use increased during the period of study, which could have contributed to the resistance patterns observed. We realize that complete prevention of cross-transmission could have changed our findings, but still the majority of cases of acquisition were considered to be from endogenous origin. Again, the increased antibiotic use during the study might have shifted the origin of resistance development to a more endogenous pattern. Most importantly, however, is our finding that even with compliance to an antibiotic rotation policy as high as 96%, there is still not enough control of antibiotic usage in the ICU to have a meaningful impact on resistance patterns. Therefore, improving infection prevention and reducing antibiotic use probably are the only meaningful strategies to control antibiotic resistance. Increasing specificity for diagnosing infections, for example by using an invasive diagnostic strategy for pneumonia7,8 and reducing duration of therapy7,30 are possibilities that have not been studied extensively yet. In addition, specific antibiotic regimens may indeed prevent the development and spread of resistance in certain settings, such as described in a neonatal ICU. Here, an empirical regimen of penicillin and tobramycin resulted in less resistance among Enterobacter species than a regimen of cefotaxim and ampicillin.31

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Reference 1. Kollef MK, Fraser VJ. Antibiotic resistance in the Intensive Care

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6. Slaughter S, Nathan C, Hayden M, Hu TC, Rice T, van Voorhis J et al. Effect of universal gown and glove vs. glove-only use on acquisition of vancomycin-resistant enterococci in a medical ICU. Proceedings of the 35th Interscience Conference on Antimicrobial Agents and Chem. 1995.

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10. Kollef MH, Vlasnik J, Sharpless L, Pasque C, Murphy D, Fraser V. Scheduled change of antibiotic classes. A strategy to decrease

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the incidence of Ventilator-Associated Pneumonia. Am J Respir Crit Care Med. 1997;156:1040-48.

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12. Gruson D, Hilbert G, Vargas F, Valentino R, Bebear C, Allery A et al. Rotation and restricted use of antibiotics in a medical intensive care unit. American Journal of Respiratory and Critical Care Medicine. 2000;162:837-43.

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16. National Committee for Clinical Laboratory Standards. Methods for disk susceptibility tests for bacteria that grow aerobically. 7th ed. NCCLS document M2-A7. Wayne, PA: National Committee for Clinical Laboratory Standards, 2000.

17. Brisse S, Milatovic D, Fluit AC, Kusters K, Toelstra A, Verhoef J et al. Molecular surveillance of European quinolone-resistant clinical isolates of Pseudomonas aeruginosa and Acinetobacter spp. using automated ribotyping. J Clin Microbiol. 2000;38:3636-45.

18. Grundmann H, Hori S, Winter B, Tami A, Austin DJ. Risk factors for the transmission of methicillin-resistant Staphylococcus aureus in an adult intensive care unit: fitting a model to the data. J Infect Dis. 2002;185:481-88.

19. Pittet D, Mourouga P, Perneger TV. Compliance with handwashing in a teaching hospital. Ann Intern Med. 1999;130:126-30.

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20. Haley RW, Bregman DA. The role of understaffing and overcrowding in recurrent outbreaks of staphylococcal infection in a neonatal special-care unit. J Infect Dis. 1982;145:875-85.

21. Fridkin SK, Pear SM, Williamson TH, Galgiani JN, Jarvis WR. The role of understaffing in central venous catheter-associated bloodstream infections. Infect Control Hosp Epidemiol. 1996;17:150-158.

22. Neuhauser MM, Weinstein RA, Rydman R, Danziger LH, Karam G, Quinn JP. Antibiotic resistance among gram-negative bacilli in US intensive care units: implications for fluoroquinolone use. JAMA. 2003;289:885-88.

23. Lipsitch M, Bergstrom CT, Levin BR. The epidemiology of antibiotic resistance in hospitals: Paradoxes and prescriptions. Proceedings of the National Academy of Sciences USA. 2000;97:1938-43.

24. Livermore DM. Multiple mechanisms of antimicrobial resistance in Pseudomonas aeruginosa: our worst nightmare? Clin Infect Dis. 2002;34:634-40.

25. Trouillet JL, Vuagnat A, Combes A, Kassis N, Chastre J, Gibert C. Pseudomonas aeruginosa ventilator-associated pneumonia: Comparison of episodes due to piperacillin-resistant versus piperacillin-susceptible organisms. Clinical Infectious Diseases. 2002;34:1047-54.

26. Scheld WM. Maintaiing fluoroquinolone class efficacy: review of influencing factors. Emerg Infect Dis. 2003; 9: 1-9.

27. John JF, Jr., Fishman NO. Programmatic role of the infectious diseases physician in controlling antimicrobial costs in the hospital. Clin Infect Dis. 1997;24:471-85.

28. Gross R, Morgan AS, Kinky DE, Weiner M, Gibson GA, Fishman NO. Impact of a hospital-based antimicrobial management program on clinical and economic outcomes. Clin Infect Dis. 2001;33:289-95.

29. Bonten MJM, Slaughter S, Ambergen AW, Hayden MK, van Voorhis J, Nathan C et al. The role of "colonization pressure" in the spread of vancomycin-resistant enterococci. An important infection control variable. Arch Intern Med. 1998;158:1127-32.

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30. Ibrahim EH, Ward S, Sherman G, Schaiff R, Fraser VJ, Kollef MH. Experience with a clinical guideline for the treatment of ventilator-associated pneumonia. Crit Care Med. 2001;29:1109-15.

31. de Man P, Verhoeven BAN, Verbrugh HA, Vos MC, van den Anker JN. An antibiotic policy to prevent emergence of resistant bacilli. Lancet. 2000;355:973-78.

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95

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96

Chapter V

Cross -Transmission of Bacteria in a Surgical Intensive Care Unit.

H.J.van Loon, M.A. Leverstein-van Hall, A.C. Fluit,M.R. Vriens, S. Brisse and J. Verhoef

Accepted for publication

Clinical Microbiology and Infection pending minor revisions

Chapter V

Abstract To evaluate the different colonization routes and the magnitude of otherwise unknown cross-transmission in our surgical ICU, we performed DNA-fingerprinting of gram-negative and Staphylococcus aureus isolates from prospectively collected surveillance cultures during a 16-month period. Automated ribotyping and Pulsed Field Gel Electrophoresis (PFGE) were used for bacterial DNA-fingerprinting. Our results showed cross-transmission of five major clones, brought to light by genotyping of routine surveillance cultures; one with Acinetobacter calcoaceticus involving four patients, one with Enterobacter cloacae involving 10 patients, two with Pseudomonas aeruginosa involving eight and 13 patients, and one with Methicillin-Susceptible Staphylococcus aureus (MSSA) involving eight patients. In conclusion, spread of bacteria in a surgical ICU occurs frequently and our results question the effectiveness of a detection system based primarily on phenotypic characteristics. A more prominent role for genotyping in first-line screening seems to offer advantages, but major drawbacks are that it is often time consuming, costly and different techniques are needed for different species.

98

Cross-Transmission of Bacteria

Introduction Nosocomial infections (NIs) are one of the most prevalent complications affecting patients in the intensive care unit (ICU) where the risk of acquiring these infections is believed to be 5 to 10 times greater than in general medical wards.1 In addition, patients in the ICU are at a two- to three-times higher risk of becoming infected with antimicrobial-resistant pathogens, such as Pseudomonas aeruginosa, Enterobacter cloacae and Staphylococcus aureus, if they are admitted for a prolonged period of time (e.g. > 7 days).2,3 Transmission and colonization with potential infectious pathogens can either be of �endogenous� origin, such as the stomach or the intestines, or of �exogenous� origin, e.g. contaminated devices or from other patients, frequently through contact with healthcare workers.4,5 Understanding of these different routes is necessary to implement the most effective prevention measures.6 For instance, in the case of cross-colonization strict adherence to infection control measures will be most effective, whereas this policy will have less effect against infections from endogenous sources. The role of the hospital environment (staff, equipment etc.) as a possible source of nosocomial pathogens remains controversial and it is believed that effective infection control measures reduce these sources.7 Outbreaks of methicillin-resistant Staphylococcus aureus (MRSA) have occurred due to contaminated environmental sources.8 Surveillance of NIs and potential spread of microorganisms is recommended to increase awareness of infection control problems and to identify areas of improvement.9 However, infection rates in ICUs often only represent the tip of the iceberg related to bacterial transmission, whereas the colonization rates are the submerged part, representing the true bacterial load present in the ward.10 The role of the microbiology laboratory is critical in the primary detection of epidemiological related microorganisms and the possibility of cross-contaminated spread of a potential pathogenic clone in different wards of the hospital. This detection is most often performed on the basis of antibiotic susceptibility patterns as a phenotypic characteristic of isolates from the same species.

99

Chapter V

Genetic typing methods are used to definitely confirm the clonal spread of a specific organism, but are seldom used during routine surveillance, because it is often time consuming, costly and different techniques are often needed for different species.11 The disadvantages of a detection system based on phenotypic characteristics such as the susceptibility pattern are that different susceptibility patterns can arise from the same strain, before and after the acquisition of resistance determinants, making it possible for a clone to escape detection, and different strains of the same species might have the same susceptibility pattern, making them a false clone.12 This means that actual spread of bacteria is unknown when strains from two or more patients are only phenotypically related. To detect true cross-transmission in an ICU one would need to perform genotypic characterization on an ongoing basis. Furthermore, to determine the value of infection control measures, surveillance and genotypic characterization of both colonizing and infecting bacteria is needed to get the best focus on the total bacterial load in the ICU. We performed DNA-fingerprinting of gram-negative and Staphylococcus aureus isolates from prospectively collected surveillance cultures during a 16-month period, to evaluate the magnitude of otherwise unknown cross-transmission in our surgical ICU. The results of this study may be used to better define infection control strategies. Materials and Methods Setting Isolates were obtained between February 2001 and October 2002 from surveillance cultures taken in the surgical ICU of the University Medical Center Utrecht (UMCU) in The Netherlands, a 1042 bed teaching hospital. This unit is an eight-bed care facility for critically ill and post-surgery patients, in need of mechanical ventilation. The ward consists of 2 separate single bedrooms, each with an anteroom; a center room with 5 beds and on the other side of the ward, another single bedroom.

100


Surveillance cultures Respiratory aspirates and rectal swabs were taken from all patients upon admission to the surgical ICU, and thereafter once a week and on discharge from the ICU. At the end of every fourth month of the study period environmental cultures were taken from predetermined locations, which were not known to the health care workers in the ICU. Sample material was inoculated on blood-, chocolate and MacConkey agar plates. The plates were inspected after 24 hours incubation at 370C in a CO2 atmosphere, except for the MacConkey agar plates, which were placed in a regular incubator. Morphologically different gram-negative colonies were selected for further identification and susceptibility testing using the Vitek I system (bioMérieux, France). When isolates were resistant to either quinolones, third generation cefalosporins, aminoglycosides, carbapenems or extended spectrum β-lactam / β-lactamase inhibitors they were stored at -800C in Microbank storage tubes (Pro-Lab Diagnostics, Neston, United Kingdom) for further study. If, after storage of a resistant isolate, a susceptible isolate of the same species was cultured from the same patient, this was also stored. Bacterial isolates Isolates included were either resistant to fluoroquinolones, piperacillin/tazobactam, third-generation cephalosporins, carbapenems or aminoglycosides. The investigation was restricted to isolates acquired during ICU stay, belonging to the Enterobacteriaceae, Staphylococcus aureus and non-fermenting gram-negative isolates such as Pseudomonas aeruginosa, Stenotrophomonas maltophilia and Acinetobacter calcoaceticus. Selection of the isolates was performed on the basis of susceptibility patterns in each individual patient. Hence, multiple isolates of the same strain with different susceptibility patterns were included per patient.

101

Chapter V

Isolate typing Automated ribotyping Gram-negative isolates were typed using the automated RiboPrinter Microbial Characterization System (Qualicon Europe Ltd., Warwick, United Kingdom) as described earlier.13 In short, a few colonies per isolate were picked from a fresh Colombia agar plate, with 5% sheep blood and suspended in sample buffer. They were heat treated at 800C for 20 minutes to inhibit endogenous DNA degradation enzymes. Lysis buffer was added and the samples were loaded into the RiboPrinter. Bacterial DNA was digested, with PvuII for Pseudomonas aeruginosa and EcoRI for the other gram-negatives, and separated by agarose gel electrophoresis, transferred directly to nylon membranes, and hybridized with a chemiluminescent labeled probe containing the rRNA operon (rrnB) from Escherichia coli. A charge-coupled-device camera was used to convert the emitting chemiluminescent light into digital information and storage in the RiboPrinter database. Each sample datum was normalized by using an adjacent standard marker set. Coefficients were calculated based upon both band position and relative intensity. Output patterns were merged into a single ribogroup by using the initial threshold similarity value of 0.93. As a function of ribogroup size, the threshold value converged until the minimal similarity value was 0.90. Each week quality control was performed by running a control batch of eight samples. Ribotype stability was always observed after the strains were passed in vitro for several months. Ribogroups were automatically given a code composed of three numbers corresponding, in order, to the instrument number (always 210), the batch number of the first isolate run that fell into this ribogroup, and the position of the isolate in the batch (1 to 8). All isolates, except the Stenotrophomonas maltophilia isolates, were typeable with the RiboPrinter system using restriction enzymes PvuII and EcoRI. The created ribogroups were checked by eye for consistency. In a few cases the software created different patterns, based on differences in background. These ribogroups were manually merged using the data management software.

102


Pulsed Filed Gel Electrophoresis (PFGE) All selected Staphylococcus aureus, Stenotrophomonas maltophilia and Pseudomonas aeruginosa isolates were typed using respectively SmaI-, DraI- and SpeI-generated restriction fragment length polymorphism patterns to asses their relationships. PFGE patterns were obtained and analyzed as described previously by Vriens et al.14 All isolates were typable, except a subgroup of the isolated Pseudomonas aeruginosa, which was identified as ribogroup 210-88-S1 after automated ribotyping. Comparison of isolates BioNumerics version 2.5 (Applied Maths, Kortrijk, Belgium) was used for cluster analysis. Clustering was performed using unweighted-pair group method with arithmetic averages (UPGMA) on the basis of the matrix of Pearson correlation coefficients of densitometric curves and an optimization parameter of 1.2% (identical to the optimization parameter in the RiboPrinter system). Definitions Isolates were considered unique when their genotype-number belonged to isolates from the same patient only. Isolates with the same genotype-number were considered possible clones when they were identified in two or more patients. Cross-transmission was assumed when the same clone was isolated in two or more patients, who acquired colonization (regardless of infection) with the identical isolate while present in the ICU during a confined period of time (episode).

103

Chapter V

Staphylococcus aureus

Stenotrophomonas m

altophilia

Pulsed Field Gel Electrophoresis

Pseudomonas aeru ginosa

Klebsiella pneumoniae

Klebsiella oxytoca

Escherichia coli

Enterobacter cloacae

Acinetobacter calcoaceticus

Autom

ated ribot yping

Bacterial species

14 27

102

19 6 19 20 25

Isolates (n)

1 14 29 10 6 13 5 6

No. U

nique types

2 4 6 - - 1 1 5

No. of possible

clones

3, 8 2

8, 13, 2, 2, 2

- - - 10

4, 2, 2

Patients involved in possible epidem

ic

The isolates were distributed am

ong the unique ribotypes and the possible clones, m

eaning that the number of types and clones contain m

ultiple isolates. Epidem

ics achieved by one of the possible clones are depicted in the last column

as the number of patients involved per episode.

Table 1: Primary patient related isolates and D

NA

-fingerprinting results obtained from

surveillance cultures of the SICU

and number of patients

involved in possible epidemics per episode.

104


Results During the study period 442 patients were admitted to the surgical ICU for more than 24 hours. There were 285 males and 157 female, with a mean age of 56.8 ± 17.9 years, a median APACHE-II score of 12.0 (range 0-33) and a mean ICU stay of 10.5 ± 19.2 days (median 3.0 days, range 1-182). In total 2520 patient related surveillance cultures, 1262 tracheal aspirates and 1258 rectum swabs, and 223 environmental cultures were taken. This resulted in 4256 unique isolates based on the different antibiotic susceptibility patterns. 667 isolates were stored and 263 were selected for DNA-fingerprinting based on their unique susceptibility patterns. In this manner 233 patient- and 30 environmental related isolates were genotyped. The typing results of the patient related isolates are illustrated in Table 1. Within the group of the Enterobacteriaceae, automated ribotyping of the Enterobacter cloacae showed 1 major clone, 210-134-S7, that led to cross-transmission involving 10 patients. This clone had eight different susceptibility patterns. In Escherichia coli only one possible clone was isolated in two patients, but no cross-transmission could be ascertained because patients were cared for in the ICU with large time intervals. Isolates of Klebsiella oxytoca and Klebsiella pneumoniae only showed unique ribotypes and did not appear to be involved in cross-transmission. Of the non-fermenters, Pseudomonas aeruginosa showed two major clones, involving episodes of colonization of 13 and 8 patients, and 4 minor clones of which only three were involved in time related episodes with colonization of two patients each. The major clones were designated ribotypes 210-88-S1 and 210-413-S2. Because of the variety in susceptibility patterns of these two types, five in the former and six in the latter, we used PFGE to further subtype these clones. Isolates of ribotype 210-88-S1 were not typable with PFGE and further subtyping of this clone was halted. Subtyping of isolates of ribotype 210-413-S2, with different antibiotic susceptibility patterns, revealed identical PFGE patterns for all isolates, confirming clonality. Acinetobacter calcoaceticus isolates were identified and showed 5 possible clones, involving two or more patients colonized with the

105

Chapter V

same strain and three cases of cross-transmission involving 4, 2 and 2 patients respectively. Stenotrophomonas maltophilia did not show any cross-transmission of importance. PFGE typing of Staphylococcus aureus showed cross-transmission of a methicillin-susceptible Staphylococcus aureus (MSSA) involving eight patients in overlapping time periods of 3 months and possible cross-transmission involving three patients during a two month period (Fig. 2). Typing results of the environmental isolates showed unique DNA-fingerprints of all isolates and did not reveal an environmental source of importance, except for one MSSA strain, which was identified in seven different locations in the ICU and from underneath the wrist watch of one of the ICU physicians. This strain was cultured at the beginning of the study period and after the necessary infection control measures were taken this strain was not cultured or identified from the environment or patient anymore during the study. Discussion Nosocomial infections (NIs) are caused by pathogens that originate from either endogenous or exogenous sources and for both sources a different approach in terms of prevention is needed.4-6 Endogenous NIs are best prevented on a patient level, by e.g. good antibiotic prophylaxis or some forms of selective digestive tract decontamination, while exogenous NIs are more sensitive to preventive strategies in infection control measures reducing cross-transmission. To recognize exogenous spread, hospital surveillance systems have been set up, but are often based on recognition of identical antibiotic susceptibility patterns. This way, a strain with different antibiotic susceptibility patterns can be missed and unrecognized epidemics can take place. In order to evaluate the magnitude of unknown episodes of cross-transmission, we performed DNA-fingerprinting of prospectively collected surveillance cultures. The results showed cross-transmission which would otherwise not have been recognized.

106


stapnew 12stapnew 18stapnew 14stapnew 15stapnew 10stapnew 17stapnew 19stapnew 24stapnew 25stapnew 1stapnew 26stapnew 13stapnew 11stapnew 22stapnew 20stapnew 21stapnew 6stapnew 7stapnew 9stapnew 8stapnew 2stapnew 3stapnew 5stapnew 4stapnew 23

1 0 08 06 04 02 00 ?

Patient related epidemic, 9 isolates of S.aureus from 8 patients.

Reference:ATCC strain 29213

Patient related epidemic, 4 isolates of S.aureus from 3 patients

8 Isolates of S.aureus from different environmental sources

Unique ribotype


1 0 08 06 04 02 00 ?





Unique ribotype


1 0 08 06 04 02 00 ?


1 0 08 06 04 02 00 ?





Unique ribotype

Figure 1: Dendrogram containing the Pulsed Field Gel Electrophoresis (PFGE) results of the methicillin-susceptible Staphylococcus aureus isolates. At the 80% similarity level, 3 different main branches can be distinguished, with isolates of different patients in confined time periods.

107

Chapter V

Our results showed cross-transmission of five major clones, brought to light by genotyping of routine surveillance cultures; one with Acinetobacter calcoaceticus involving four patients, one with Enterobacter cloacae involving 10 patients, two with Pseudomonas aeruginosa involving eight and 13 patients, and one with MSSA involving eight patients. There was an obvious bias in the selection of our isolates, because our isolates were resistant to either fluoroquinolones, piperacillin/tazobactam, third-genereation cephalosporins, carbapenems or aminoglycosides. This might have given the strains, represented by our isolates, a survival benefit because many patients in the ICU received the broadspectrum antibiotics that were mentioned above. However, the cross-transmissions were not detected on a �real time� basis by the microbiology laboratory and the department of hospital hygiene, because most of the isolates harboured different phenotypic susceptibility patterns. Natural distribution of different genotypes among different species will always remain the subject of discussion and thus the question as to whether clonal spread has actually occurred due to cross-transmission or due to independent colonization of different patients always remains debatable.11 Another limitation of this study is that we only observed colonization and not infection, which may reduce the clinical impact of this study. On the other hand, if we only collected and described data associated with infections we would only be looking at the tip of the iceberg and we would not be able to answer questions concerning the endogenous or exogenous origin of the infectious complications.15 Besides, when horizontal gene transfer is concerned, infections are not an obligatory phenomenon. Colonization alone will suffice. It is most likely that inadequate hand hygiene has led to the transport and spread of the bacteria involved in the epidemics during this study, stressing once more the need for optimal hand hygiene. In conclusion, spread of bacteria in a surgical ICU is a frequent occurrence and our results question the effectiveness of a detection system based primary on phenotypic characteristics. A more prominent role for genotyping in first-line screening seems to offer

108


advantages, but major drawbacks are that it is often time consuming, costly and different techniques are needed for different species. Therefore, we feel that future epidemiological research should be directed into developing a more secure detection program of cross-transmissional spread of pathogenic microorganisms, with a more prominent role for quicker and cheaper genotyping techniques, for example nucleotide sequence-based multitarget identification16, to give good guidance for infection control measures in our battle against the resistant microorganisms.

109

Chapter V

References 1. Weber DJ, Raasch R, Rutala WA. Nosocomial infections in the

ICU: the growing importance of antibiotic-resistant pathogens. Chest 1999; 115:S34-S41.

2. Fridkin SK. Increasing prevalence of antimicrobial resistance in intensive care units. Cirt Care Med 2001; 29(Suppl 4):N64-N68.

3. Martin MA. Nosocomial infections in intensive care units: an overview of their epidemiology, outcome, and prevention. New Horiz 1993; 1:162-71.

4. Torres A, El-Ebiary M, González J, et al. Gastric and pharyngeal flora in nosocomial pneumonia acquired during mechanical ventilation. Am Rev Respir Dis 1993; 148:352-7.

5. Grundmann H, Kropec A, Hartung D, et al. Pseudomonas aeruginosa in a neonatal intensive care unit: reservoirs and ecology of the nosocomial pathogen. J infect Dis 1993; 168:943-7.

6. Bergmans DCJJ, Bonten MJM, van Tiel FH, et al. Cross-colonization with Pseudomonas aeruginosa of patients in an intensive care unit. Thorax 1998; 53:1053-8.

7. Bertrand X, Thouverez M, Talon D, et al. Endemicity, molecular diversity and colonisation routes of Pseudomonas aeruginosa in intensive care units. Intensive Care Med 2001; 27:1263-8.

8. Bures S, Fishbain JT, Uyehara CFT, Parker JM, Berg BW. Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control 2000; 28:465-70.

9. Weist K, Polleg K, Schulz I, Rüden H, Gastmeier P. How many nosocomial infections are associated with cross-transmission? A prospective cohort study in a surgical intensive care unit. Infect Control Hosp Epidemiol 2002; 23:127-32.

10. Bonten MJM, Bergmans DCJJ, Speijer H, Stobberingh EE. Characteristics of polyclonal endemicity of Pseudomonas aeruginosa colonization in intensive care units: implications for infection control. Am J Resp Crit Care Med 1999; 160:1212-19.

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11. Grundmann H, Hahn A Ehrenstein B, Geiger K, Just H, Dashner FD. Detection of cross-transmission of multiresistant gram-negative bacilli and Staphylococcus aureus in adult intensive care units by routine typing of clinical isolates. Clin Microbiol Infect 1999; 5:355-63.

12. Sanders EW jr, Sanders CC. Enterobacter spp.: pathogens poised to flourish at the turn of the century. Clin Microbiol Rev 1997; 10:220-41.

13. Brisse S, Milatovic D, Fluit AC, Kusters K, Toelstra A, Verhoef J, Schmitz FJ. Molecular surveillance of European quinolone-resistant clinical isolates of Pseudomonas aeruginosa and Acinetobacter spp. Using automated riboprinting. J Clin Microbiol 2000; 38:3636-45.

14. Vriens MR, Fluit AC, Troelstra A, Verhoef J, van der Werken C. Is methicillin-resistant Staphylococcus aureus more contageous than methicillin-susceptible S. aureus in a surgical intensive care unit? Infect Control Hosp Epidemiol 2002; 23:491-4.

15. Langer M, Carretto E, Haeusler EA. Infection control in ICU: back (forward) to surveillance samples? Intensive Care Med 2001; 27:1561-63.

16. Vinayagamoorthy T, Mulatz K and Hodkinson R. Nucleotide sequence-based multitarget identification. J Clin Microbiol 2003; 41:3284-92.

111

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112

Chapter VI

A Highly Epidemic Enterobacter cloacae Clone.

H.J. van Loon, H.E.M. Blok, A.C. Fluit,

J. Verhoef, E. Mascini and M.A. Leverstein-van Hall

Accepted for publication in part Journal of Hospital Infection

Chapter VI

Abstract We describe the spread and evolution of an Enterobacter cloacae that was present in our hospital over a two year period, when an increase in infections caused by tobramycin-resistant E. cloacae was observed from September 2001. Susceptibility testing and genotyping was performed on all available E. cloacae isolates between September 2001 and June 2003. The isolates from 103 patients were genotyped by PFGE, a major E. cloacae clone (clone E) was observed in the isolates from 66 patients, while the isolates from the remaining 37 patients were unique. Susceptibility testing resulted in 15 different susceptibility patterns belonging to isolates from the same genotypic E. cloacae clone. In a relatively short period of time this E. cloacae clone had managed to spread to many different hospital wards, despite our routine infection control measures, such as: Isolation precautions for patients harbouring aminoglycoside-resistant microorganisms. This clone had a unique capacity to spread and its’ epidemic characteristics are currently under investigation.

114

Highly Epidemic Enterobacter cloacae

Introduction Enterobacter cloacae is a relatively recent pathogen and is capable of causing opportunistic infections, especially in patients during long periods of hospitalization and treatment with broad-spectrum antibiotics.1,2 Probably the increase in clinical presence of E. cloacae during the 1970’s was due to an increasing number of patients predisposed to opportunistic infections which needed treatment with antibiotics, such as cephalosporins. The high mutation frequency of E. cloacae (105-107) to resistance of second- and third generation cephalosporins has made this species an increasing problem in hospitals and intensive care units (ICUs) and increased awareness has made E. cloacae subject of increasing numbers of reports on their presence in ICUs.3,4 In 2001, we observed a rise in incidence of Enterobacter cloacae strains throughout the hospital. Some of these strains were multiresistant, while others were still susceptible to a variety of antibiotics. Because of the many different resistance patterns, an outbreak was not immediately contemplated. In our hospital it is policy that patients are cared for in barrier-nursing when colonized with an ESBL positive and/or an aminoglycoside- resistant Gram-negative microorganism. Therefor, as the incidence of patients colonized with E. cloacae continued to rise, we decided on a hospital wide surveillance study and to genotype the isolated E. cloacae strains, despite their phenotypic differences. Patients colonized with multiresistant E. cloacae were treated in barrier-nursing. During our study an Enterobacter cloacae clone was found, which had spread throughout many different hospital wards and demonstrated many different antimicrobial susceptibility patterns.

115

Chapter VI

Materials and methods Setting The University Medical Center Utrecht (UMCU) in the Netherlands is a 1042-bed tertiary care teaching hospital where all medical disciplines are represented. Each discipline has it own ward(s) with its own staff. There are four ICUs available for; general surgery, cardiac and neurosurgical patients. The laboratory of diagnostic bacteriology processes about 100,000 specimen a year and works in close collaboration with the department of hospital hygiene and infection control. Cultures Clinical and surveillance specimens were identified and susceptibility tests were performed according to standard operating procedures based on common microbiological practices. Sample material was inoculated on blood-, chocolate and MacConkey agar plates. The plates were inspected after 24 hours incubation at 370C in a CO2 atmosphere, except for the MacConkey agar plates, which were placed in a regular incubator. Morphologically different gram-negative colonies were selected for further identification and susceptibility testing using the Vitek I system (bioMérieux, France). Additional susceptibility tests for levofloxacin and cefpirome were performed by means of the disk-diffusion method, according to the National Committee for Clinical Laboratory Standards (NCCLS).5 Isolates were regarded either as being susceptible or resistant (these also included the intermediate susceptible isolates). All available E. cloacae isolates were typed and characterized by pulsed field gel electrophoresis (PFGE) using XbaI in a modified protocol of the PFGE method as described previously.6,7,8

116


Comparison of isolates BioNumerics version 2.5 (Applied Maths, Kortrijk, Belgium) was used for cluster analysis. Clustering was performed using unweighted-pair group method with arithmetic averages (UPGMA) on the basis of the matrix of Pearson correlation coefficients of densitometric curves and an optimization parameter of 1.2% (identical to the optimization parameter in the RiboPrinter system). Isolates were considered to have a unique genotype when the PFGE type belonged to isolates from the same patient only. Results Enterobacter cloacae in the UMC-U, from September 2001 until December 2002 Clinical microbiologists in the UMC-U observed an increase in the number of multi-resistant E. cloacae isolated from clinical specimen. This observation was followed by a retrospective analysis, which demonstrated positive culture results for E. cloacae in 631 clinical specimen of admitted patients from September 2001 until December 2002. From 51 of theses patients a tobramycin-resistant E. cloacae was isolated from the following clinical sites: sputum (28), urine (10), wounds (7), blood (1), aortic valve (1), prosthetic joint (1), cerebrospinal fluid (1), bone (1), and a vaginal swab (1). Conform with our hospital policy, each patient that yielded a multi-resistant E. cloacae strain was cared for in barrier-isolation. However, clinical microbiologists and infection control nurses shared the impression that despite the implementation of this infection control policy the number of resistant E. cloacae isolates was still growing. Hence it was decided to perform surveillance cultures in those wards where patients colonized with tobramycin-resistant E. cloacae were treated.

117

Chapter VI

PFGE types of tobramycin-resistant E. cloacae obtained from December 2002 – May 2003. Of the 631 E. cloacae strains obtained from clinical material collected in 2001/2002, isolates from 55 patients were still available for typing, of which 37 patients were colonized with tobramycin-resistant strains of E. cloacae. By screening patients in the various wards from December 2002 on, 48 additional patients colonized with E. cloacae were identified, of which 37 patients were colonized with tobramycin-resistant strains. The isolates from all 103 patients were genotyped by PFGE and demonstrated the presence of a major E. cloacae clone in the isolates from 66 patients (Fig. 1), 31 from the period before December 2002 and 35 patients from thereafter. Figure 1 illustrates the dendrogram containing the PFGE patterns of the 103 patients colonized with multi-resistant E. cloacae during our study period. The pattern of the E. cloacae clone appears to be clearly present in the upper portion of the dendrogram, at a similarity interval of more than 80%. The remaining 37 patients were all colonized with a unique PFGE-type E. cloacae and were regarded as epidemiological unrelated.

118


Genotype E

Dic e (O pt:1 .0 0 % ) (T ol 2 .0 % -2 .0 % ) (H > 1 .0% S> 1 .0 % ) [0 .0% - 1 00 .0 % ]P FGE

100

90

80

70

60

PFGE

02-347

V2296

02-505

02-034

02-264

V522

02-371

02-001

02-228

02-225

02-412

02-043

02-513

02-477

02-106

02-484

02-123

02-270

E118

03-068

02-014

03-070

03-031

03-155

03-152

02-050

02-321

02-354

02-395

02-022

03-271

02-041

W 551

03-324

03-317

03-387

03-381

03-520

03-326

03-089

03-375

03-069

03-072

03-289

03-024

03-402

02-492

03-019

02-382

02-360

02-512

01-273

02-464

03-394

02-107

02-301

02-195

03-410

02-507

02-475

02-367

03-490

03-504

02-315

03-471

03-015

V2434

03-372

E020

V1737

03-299

03-312

02-314

V451

01-198

03-325

V2564

03-307

03-295

02-406

03-508

V357

V2112

E017

03-329

E012

02-448

E021

03-510

E019

U 2786

02-285

01-197

02-008

V2158

V338

E018

V1764

W 005

03-305

03-304

E001

03-322

Bachttour

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Bakk ers

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Unique Genotypes

Figure 1: Dendrogram containing the Pulsed Field Gel Electrophoresis (PFGE) results of the 103 patients colonized with multi-resistant E. cloacae. Above the 80% similarity level, in the upper part of the figure, a single clone E can be observed.

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Susceptibility patterns of E. cloacae clone E Susceptibility testing of 99 different isolates of the designated E. cloacae clone was performed. This resulted in 15 different susceptibility patterns belonging to the same genotypic E. cloacae clone. Table 1 illustrates the different phenotypes.

Phenotype Cip Cot Gen Tob Ami Nit Tet Mer N 1 R R R R S R R S 10 2 R S R R S R R S 14 3 R S R R S S R S 13 4 R R S R R R R S 2 5 R R S R S R R S 10 6 R S S R S R R R 1 7 R S S R S R R S 18 8 R S S R S R S S 1 9 R R S R S S R S 3

10 R S S R S S R S 18 11 R S S R S S S S 2 12 S R R R R S R S 1 13 S S R R S R R S 1 14 S S R R S S R S 3 15 S S S R S S R S 2

Cip: ciprofloxacin; Cot: cotrimoxazole; Gen: gentamicin; Tob: tobramycin; Ami: amikacin; Nit: nitrofurantoin ; Tet: tetracyclin; Mer: meropenem. R: resistant; S: susceptible.

Table 1: Different antibiotic susceptibility patterns of the designated E. cloacae clone.

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Spread of E. cloacae clone E in the hospital Figure 2, on the next page, depicts the distribution and spread of the patients colonized with clone E between the different hospital wards. Forty-eight patients had been treated in one of the surgical wards. Twenty-two of these patients stayed at the surgical ICU and remained on surgical wards only, while twenty-six patients were transferred to other wards, enabling them to spread the clone to other patients. (e.g. six patients were transferred from the Surgical ICU to Cardiac ICU; two patients from the Cardiac ICU became colonized with clone E and were transferred to the Anesthesiology ICU. This ICU also housed four other patients with clone E from the Surgical ICU; another patient in the Anesthesiology ICU became colonized with clone E and remained on that ward, while seven other patients became colonized and were transferred to the Neurological wards; two patients were transferred from the Surgical ICU to the Anesthesiology ICU and afterwards to the Neurological wards.)

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Surgical ICU

22

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Figure 2: Distribution of patients colonized with the E. cloacae clone E, across the different wards of the hospital.

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Discussion In this paper the spread of a highly epidemic clone of E. cloacae is described. Because of a presumed rise in infections caused by a tobramycin-resistant E. cloacae in September 2002, surveillance cultures were instigated in the different wards of our hospital. All available multi-resistant E. cloacae (especially tobramycin-resistant) isolated from September 2001 until June 2003 were subjected to PFGE. Out of 103 patients colonized with an E. cloacae strain, 66 (68%) appeard to be colonized with a virulent E. cloacae clone. This clone was able to disseminate rapidly through the hospital and was not recognized by our classic hospital surveillance system, because of the initially low incidence of infections, the long intervals between consecutive infections, the large variety of infections (ranging from abdominal infections to meningitis), the frequent transfer of patients from one ward to another, the differences in susceptibility patterns expressed by the E. cloacae clone and the large number of staff working part-time in combination with their frequent change of work area leading to an underestimation of the problem. Only after the strains were typed it became clear that an epidemic had taken place and that barrier-nursing alone was not enough to contain the spread of this clone. Point of discussion will always be the possibility that patients, or a small cluster of patients yielding a unique strain were never transferred to another ward and therefore remained unique and contained. Nevertheless, these strains did not spread among (many) patients in their own ward/ICU either. Thus, it is highly likely that the E. cloacae clone is different from other strains in its capacity to disseminate. The E. cloacae clone could very well have acquired some virulence properties; or another explanation could be, that the 15 different resistance patterns made this clone more easily selected by the large quantities of antibiotics that are used in the ICUs.

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In conclusion, some important lessons can be drawn from this study, (1) probably bacteria are able to spread in a hospital environment on a frequent basis, often unnoticed, (2) only when strains become resistant they are picked-up by our infection control surveillance system and are recognized as a potential outbreak,9 (3) there is a clear difference in epidemicity between strains. Further studies are needed to answer the question why certain strains are more contagious than other strains. This is an important question and when answered infection control measures can be taken directly towards these specific strains with high epidemicity. Furthermore, it is imperative to study the role of antibiotics in the transfer of bacteria. In a setting where many patients receive antibiotics (e.g. ICU), it is likely that only multi-resistant bacteria are able to spread. Which antibiotics favor the spread of multi-resistant strains the most is not known. The E. cloacae clone in this study was first recognized in our hospital during a study where antibiotics were cycled.10 It is possible that the antibiotics used in this study have favoured the selection of clone E. On the other hand it is also possible that clone E was introduced in our hospital as a susceptible strain and during circulation in our hospital, the strain became resistant (either by mutation or by uptake of resistance genes). Further studies are underway to answer these important questions.

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References 1. Crowe M, Ispahani P, Humphreys H, Kelley T, Winter T.

Bacteremia in the adult intensive care unit of a teaching hospital in Nottingham, UK, 1985-1996. Eur J Clin Microbiol Infect Dis 1998; 17:377-84.

2. Liu SC, Leu HS, Yen MY, Lee PI, Chou MC. Study of an outbreak of Enterobacter cloacae sepsis in a neonatal intensive care unit: the application of epidemiologic chromosome profiling by pulsed field gel electrophoresis. Am J Infect Control 2002; 30:381-5.

3. Gaston MA. Enterobacter: an emerging nosocomial pathogen. J Hosp Infect 1988; 11:197-208.

4. Chow JW, Yu VL, Shlaes DM. Epidemiologic perspectives on Enterobacter for the infection control professional. Am J Infect Control 1994; 22:195-201.

5. National Committee for Clinical Laboratory Standards. Methods for disk susceptibility tests for bacteria that grow aerobically. 7th ed. NCCLS document M2-A7. Wayne, PA: National Committee for Clinical Laboratory Standards, 2000.

6. Leverstein-van Hall MA, Box ATA, Blok HEM, Paauw A, Fluit AC, Verhoef J. Evidence of extensive interspecies transfer of integron-mediated antimicrobial resistance genes among multidrug-resistant Enterobacteriaceae in aclinical setting. J Infect Dis 2002; 186:49-56.

7. Chetchotisakd P, Phelps CL, Hartstein AI. Assesment of bacterial cross-transmission as a cause of infection in patients in intensive care units. Clin Infect Dis 1994; 18:929-37.

8. Tenover FC, Arbeit RD, Goering RV, et al. Interpreting chromosomal DNA restriction patterns produced by pulsed-field gel electrophoresis: criteria for bacterial strain typing. J Clin Microbiol 1995; 33:2233-39.

9. van Loon HJ, Leverstein-van Hall MA, Fluit AC, et al. Cross -Transmission of Microorganisms on a Surgical Intensive Care Unit. Chapter 5 of this thesis, submitted for publication.

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10. van Loon HJ, Vriens MR, Fluit AC, et al. Antibiotic rotation and development of gram-negative antibiotic resistance: the cyclone trial. Chapter 4 of this thesis, submitted for publication.

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The Evolution of Pseudomonas aeruginosa During Antibiotic Rotation in a Medical

Intensive Care Unit. The RADAR-trial.

D.T. Tsukayama, H.J. van Loon, C. Cartwright, B. Chmielewski, A.C. Fluit,

Chr. van der Werken and J.Verhoef

Published International Journal of Antimicrobial Agents

2004; 24:339-45

Chapter VII

Abstract Bacterial spread between patients, may contribute to the high prevalence of antibiotic-resistant pathogens within ICUs. The aim of this study was to evaluate the fate of Pseudomonas aeruginosa during the different antibiotic regimens. Susceptibility patterns and genotyping were performed to determine whether there was a predominant clone, and to track the spread of resistant strains within the unit. Twenty-eight different ribotypes were found among 82 Pseudomonas isolates. Four ribotypes accounted for 42 (51%) isolates and were designated the ‘major clones’ occurring throughout multiple cycles. The ribotypes with multiple occurrences were more resistant to antibiotics than ribotypes, which appeared only once. The correlation of antibiotic use with antibiotic resistance and the finding of a large number of ribotypes suggests that de novo development of antibiotic resistance is a likely event in Pseudomonas aeruginosa. In addition, ribotypes associated with antibiotic resistance appear to have a survival advantage and can become frequent colonizers in the ICU.

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Pseudomonas aeruginosa and Rotating Antibiotics

Introduction Antibiotic resistance among bacteria has been a constant, and seemingly accelerating, problem in the management of patients with infections. Antimicrobial resistance is of special concern in the setting of the intensive care unit (ICU), where resistance rates are higher than in other hospital wards or the community.1,2 There are many factors that contribute to the high rate of antibiotic resistance in the ICU, but one factor of major impact is the ecological pressure exerted by high usage of antibiotics in critically ill patients.3 There is an urgent need to reverse this trend of increasing antibiotic resistance, which, left unimpeded, threatens to significantly compromise our ability to treat patients with severe infections. The most common response to resistance is to restrict the use of the antibiotics to which antimicrobial resistance has developed, or restriction of the antibiotics felt to lead to resistance. One problem with this solution is that, as other antibiotics are used in place of the restricted agent, new resistance patterns may emerge.4 A proposed alternative strategy to control antibiotic resistance is antibiotic cycling.5,6 As the name implies, for a given indication one antibiotic regimen is used for a predefined period of time, to be replaced by other agents in rotation. The rationale is that limiting the duration of antibiotic pressure by any single antibiotic or antibiotic class may decrease the development of resistance. It must be recognized however, that different strategies may be needed to control antibiotic resistance depending on the underlying mechanism. Limiting antibiotic use may decrease mutation rates of bacteria, but if resistance is the result of the spread of one bacterial clone throughout the unit, strict attention to infection control measures will be the more effective intervention. To determine whether antibiotic resistance in a medical ICU could be altered by antibiotic cycling, we instituted an antibiotic cycling study to rotate broad-spectrum empiric therapy between a regimen of quinolones plus clindamycin or metronidazole alternating with a second regimen using beta-lactams. The study was conducted for 16 months, and consisted of 4 cycles of 4 months duration. Ciprofloxacin or levofloxacin was used during cycles 1 and 3, and piperacillin-tazobactam and other beta-lactams during cycles 2

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and 4. We named this study RADAR, Rotating Antibiotics to Decrease Antimicrobial Resistance. As part of the study, surveillance cultures from the respiratory tract and rectum were obtained weekly from patients to monitor the prevalence of antibiotic resistant microorganisms. Pseudomonas aeruginosa, a frequent cause of ICU infections7,8, was the most frequently recovered Gram-negative pathogen during RADAR and therefore, the aim of this study was to examine the evolution of antibiotic-resistance and spread of Pseudomonas aeruginosa during a rotational antibiotic policy in a United States medical ICU. Methods Description of the ICU The unit studied was a 12 bed medical ICU at Hennepin County Medical Center in Minneapolis, Minnesota. The shape of the ward is square, with the entrance on one side and 4 beds each on the other three sides, numbered 1-12 starting from the left of the entrance; each bed is placed in a cubicle separated from the rest of the ward. Nurses work in shifts of 8-12 hours, usually each nurse has one or two patients. During the 16 month study there were 1371 patients admitted to the unit and a total of 4780 patient-days. Antibiotic cycling Empiric antibiotic therapy was rotated between two different regimens. The regimen of first choice empiric treatment used in cycles 1 and 3 was ciprofloxacin or levofloxacin plus clindamycin or metronidazole. The regimen used in cycle 2 and 4 was piperacillin-tazobactam. Other antibiotics were permitted as deemed necessary by the treating physician in case antimicrobial resistance to one of the first choice antimicrobial drugs. When broad-spectrum therapy was no longer needed, the antibiotics were changed to the appropriate narrow-spectrum agents. The project was approved by the Human Subjects Research Committee. The total amount of antibiotics used in each

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cycle was recorded as units of defined daily doses (DDD) and compared to the susceptibility patterns of bacteria obtained from surveillance cultures (Table 1). Infection control measures Infection control policies call for handwashing before each patient encounter, and contact precautions (gown, glove, and if needed, eye protection and mask) for patients colonized with methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus spp., or multiple antibiotic resistant Gram-negative bacilli. No special infection control measures were instituted for this study. Surveillance cultures Cultures of respiratory secretions and rectum were obtained weekly on Tuesday morning from all patients who were in the ICU at that time. This included repeat cultures on patients who remained in the unit for more than one week. Informed consent was waved, because surveillance cultures were part of routine hygiene quality control, conventional antibiotic therapy was used and optimal patient care was maintained. Clinical cultures Hospital charts were reviewed and bacterial isolates from all clinical cultures were recorded. Data was gathered detailing age and gender, antibiotic susceptibility of the isolates, and, for each patient, the number of antibiotics used and the number of ventilator days. Antibiotic Susceptibility Testing Microtiter dilution plates were used to determine the minimal inhibitory concentration of all Gram-negative species to ceftriaxone, ceftazidime, piperacillin-tazobactam, imipenem-cilastatin, tobramycin, trimethoprim-sulfamethoxazole, ciprofloxacin, and levofloxacin. Antimicrobial susceptibility and resistance was

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determined according to NCCLS standards. In addition a Multi-Drug Resistance (MDR) index was defined for Pseudomonas aeruginosa. A value of 1 was assigned for susceptibility to each of six antibiotics (ceftazidime, piperacillin-tazobactam, imipenem-cilastatin, tobramycin, ciprofloxacin, and levofloxacin), and totaled. An isolate susceptible to all 6 antibiotics would have an MDR index of 6, while one which was resistant to all 6 antibiotics would have an MDR index of 0. Bacterial isolates Between May 2000 and August 2001 a total of 96 Pseudomonas aeruginosa isolates were collected at Hennepin County Medical Center as part of the study: All recovered isolates were sent for ribotyping to the Eijkman-Winkler Institute for Clinical Microbiology, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands. No more than two isolates per patient, a tracheal aspirate and a rectal swab, were included. They were sent in protective bio-containers. On arrival the isolates were immediately cultured on Columbia agar plates, with 5% sheep blood. Ten isolates were not recoverable after transport and the remaining isolates were reidentified using the Vitek system (BioMérieux Benelux BV, s’ Hertogenbosch, The Netherlands). After reidentification 82 isolates were confirmed P. aeruginosa and stored at -800C in Microbank storage tubes (Pro-Lab Diagnostics, Neston, United Kingdom) for further study. Automated ribotyping Eighty-two isolates were typed using the automated RiboPrinter Microbial Characterisation System (Qualicon Europe Ltd., Warwick, United Kingdom) as described earlier.9 In short, a few colonies per isolate were picked from a fresh Colombia agar plate, with 5% sheep blood and suspended in sample buffer. They were heat treated at 800C for 20 minutes to inhibit endogenous DNA degradation enzymes. Lysis buffer was added and the samples were loaded into the RiboPrinter. Bacterial DNA was digested with PvuII and seperated by agarose gel electrophoresis, transferred directly to nylon membranes,

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and hybridized with a chemiluminescent labeled probe containing the rRNA operon (rrnB) from Escherichia coli. A charge-coupled-device camera was used to convert the emitting chemiluminescent light into digital information and storage in the RiboPrinter database. Each sample datum was normalized by using an adjacent standard marker set. Coefficients were calculated based upon both band position and relative intensity. Output patterns were merged into a single ribogroup by using the initial threshold similarity value of 0.93. As a function of ribogroup size, the threshold value converged until the minimal similarity value was 0.90. Each week quality control was performed by running a control batch of eight samples. Ribotype stability was always observed after the strains were passaged in vitro for several months. All 82 isolates were typeable with the RiboPrinter system using restriction enzyme PvuII. The created ribogroups were checked by eye for consistency. In a few cases the software created different patterns, based on differences in background. These ribogroups were manually merged using the data management software. Ribotype numbers were created by matching the isolates with the ribotype groups available in the local database of the Eijkman-Winkler Institute. Data analysis BioNumerics version 2.5 (Applied Maths, Kortrijk, Belgium) was used for cluster analysis. Clustering was performed using unweighted-pair group method with arithmetic averages (UPGMA) on the basis of the matrix of Pearson correlation coefficients of densitometric curves and an optimization parameter of 1.2% (identical to the optimization parameter in the RiboPrinter system).

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Cycle CIP LEV PTZ CTZ

IMI TOB 1 DDD 186 236 47 117 65 17 Resistant, % 73 64 45 45 32 5 2 DDD 162 124 220 93 136 47 Resistant, % 42 42 58 47 40 7 3 DDD 284 237 100 25 53 16 Resistant, % 35 35 18 19 44 6 4 DDD 131 103 206 81 130 19 Resistant, % 82 73 86 64 59 36

Total DDD 763 700 573 315 404 99 Resistant, % 53 58 54 44 44 12

CIP: ciprofloxacin LEV: levofloxacin PTZ: piperacillin-tazobactam CTZ: ceftazidime IMI: imipenem TOB: tobramycin

Table 1: Amount of antibiotic use in daily defined dosage (DDD) and Pseudomonas resistance by cycle as a percentage of all isolates.

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Results Antibiotic use Table 1 illustrates the antibiotic use in daily-defined doses (DDD) throughout the different cycles and illustrates quinolones (ciprofloxacin and levofloxacin) most frequently prescribed during cycles 1 and 3, whereas piperacillin-tazobactam and other beta-lactam antibiotics were more frequently prescribed during cycles 2 and 4. However, the use of quinolones and piperacillin-tazobactam or other antibiotics was not completely restricted during any period throughout the study. Carbapenem and aminoglycoside use and resistance are also shown in table 1. A trend in the correlation of percentage of piperacillin-tazobactam-resistant Pseudomonas aeruginosa per cycle with antibiotic use (Figure 1) was seen, but was not statistically significant. Total quinolone resistance varied from 37% (cycle 3) to 77% (cycle 4). This did not correlate with the antibiotic usage of the quinolones during the different cycles. Over the course of the entire study higher antibiotic use correlated to higher antibiotic resistance (Figure 2).

47

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206

0

50

100

150

200

250

1 2 3 4

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DD

D

0102030405060708090100

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esistance

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Figure 1: Relationship of antibiotic use (DDD) of piperacillin-tazobactam (PIP/TAZ) and percent resistance of Pseudomonas by cycle.

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0102030405060708090

100

0 200 400 600 800 1000

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TOB: tobramycin; CTZ: ceftazidime; IMI: imipenem PIP/TAZ: piperacillin-tazobactam; LEV: levofloxacin; CIP: ciprofloxacin

Figure 2: Relationship of total amount of use (DDD) of the antibiotics tobramycin, ceftazidime, imipenem, piperacillin-tazobactam, levofloxacin and ciprofloxacin to the percent resistance of Pseudomonas.

Ribotypes To evaluate the development of resistance and the spread of Pseudomonas aeruginosa, the most frequently isolated Gram-negative pathogen in the ICU during this study, these strains were ribotyped. Of the total of 82 Pseudomonas aeruginosa isolates that were recovered after transport to the Netherlands, there were 27 different ribotypes, 14 of which occurred only once and were obtained from 49 different patients. Susceptibility to ciprofloxacin among all isolates was 42 %, and susceptibility to piperacillin-tazobactam was 46 %. The MDR index was 3.32. The ribotypes obtained are illustrated in figure 3. The number of isolates belonging to each ribotype ranged from 1 to 18.

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Figure 3: Automated ribotyping patterns of the 82 Pseudomonas aeruginosa isolates.

Ribotype 14

Ribotype 40

Ribotype 75

Ribotype 3

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Distribution of the major clones There were 4 ribotypes consisting of 5 or more isolates. These types were defined as the ‘major clones’ (ribotype 3, 14, 40, 75). Figure 4 shows the distribution of these ‘major clones’ over the different cycles. Ribotype 3 was found in 18 isolates from 9 patients. Susceptibility to ciprofloxacin among these isolates was 13%, and susceptibility to piperacillin-tazobactam was 33%. The MDR index was 2.4. This ribotype was recovered from patients during cycles 1 (n=4), 2 (n=3), and 4 (n=3). One patient was present during cycle 1 and the beginning of cycle 2. It first appeared in a patient in bed 8, then was later found in patients in beds 11 and thereafter in bed 7, 12 and 10. Ribotype 14 was found in 7 isolates from 6 patients. Susceptibility to ciprofloxacin among these isolates was 71%, and susceptibility to piperacillin-tazobactam was 57%. The MDR index was 4.29. This ribotype was recovered from patients during cycles 1 (n=1), 2 (n=1), 3 (n=3) and 4 (n=1). It appeared first in patients in bed 4, and was later found in patients in bed 9, 6 and 10. Ribotype 40 was found in 8 isolates from 3 patients. Susceptibility to ciprofloxacin among these isolates was 13%, and susceptibility to piperacillin-tazobactam was 13%. The MDR index was 2.00. This ribotype was recovered from patients during cycles 2 (n=1), 3 (n=1) and 4 (n=1). It appeared first in patients in bed 5, and was subsequently found in patients in bed 4 and 2. Ribotype 75 was found in 12 isolates from 6 patients. Susceptibility to ciprofloxacin among these isolates was 42%, and susceptibility to piperacillin-tazobactam was 50%. The MDR index was 3.17. This ribotype was recovered from patients during cycles 3 (n=3) and 4 (n=4). One patient was present in both cycle 3 and 4. It first appeared in patients in bed 4, and later in patients in bed 9, 1, 8, 10 and 6.

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Distribution of the major clones

0

1

2

3

4

5

1 2 3 4

Cycle

No.

pat

ient

s Type 3Type 14Type 40Type 75

Figure 4: Distribution of the major clones expressed in the number of patients colonized per cycle

Ribotypes and resistance by Cycle Distribution of all ribotypes through the different cycles is summarized in Table 2. During cycle 1 and 3 a higher percentage of quinolone resistance was observed compared to piperacillin-tazobactam resistance. A higher resistance rate to piperacillin-tazobactam was observed during cycle 2, compared to quinolone resistance. Both quinolone and piperacillin-tazobactam resistance rates were highest during cycle 4, when ribotype 3 appeared again and all major clones were present.

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MD

R

3.14

3.61

4.41

1.95

Pip/

Tazo

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58%

18%

86%

Qui

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stan

ce

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42%

35%

82%

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es

3,14

3,14

,40

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3,14

,40,

75

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otyp

es

3,14

,16,

21,7

3,74

,87,

89,1

04

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,40,

56,5

7,59

,63,

65,6

6,69

,72,

98

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4,39

,40,

43,5

8,60

,75,

83

1,3,

10,1

4,40

,58,

75

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15

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Cyc

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Cyc

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Clinical Cultures Clinical cultures were obtained for fever or suspected infection in all 49 patients during their ICU stay. Pseudomonas was recovered in 23 patients. Among these isolates the rate of resistance to piperacillin/tazobactam was 34% and ciprofloxacin susceptibility was 45%. This was not significantly different from the resistance rate of isolates recovered hospital-wide, which was 21% for piperacillin-tazobactam, and 32% for ciprofloxacin, 32%. Resistance to piperacillin-tazobactam was significantly less among clinical isolates than among surveillance isolates (54%, p < 0.43). There was no significant difference in resistance of clinical isolates of ciprofloxacin to either surveillance isolates or hospital-wide isolates. Hospital-wide resistance was significantly different from surveillance resistance for both piperacillin-tazobactam (p < 0.001) and ciprofloxacin (p < 0.002). Compared to the 26 patients who did not have Pseudomonas in any clinical cultures, there was a significant difference in the number of antibiotics used (3.92 ± 2.02 for those without Pseudomonas in clinical cultures versus 5.36 ± 2.36 for those with clinical culture positive for Pseudomonas) but no difference in ventilator days.(14.04 ±16.20 versus 20.08 ± 14.47). Discussion Pseudomonas aeruginosa was the most frequently (40%) recovered Gram-negative species during RADAR and remains one of the most significant pathogens in nosocomial infections, especially in patients treated in the ICU. Its ability to acquire antibiotic resistance is well known. Given that the number of antibiotic agents with activity against this organism is limited from the outset, any resistance development in Pseudomonas is a potential problem. This study demonstrates that the mechanism underlying the appearance of resistant Pseudomonas isolates in the ICU is likely to be a combination of both development of resistance and spread of resistant clones. There were a total of 27 different ribotypes found among 82 isolates, indicating that P. aeruginosa in the ICU comes from a variety of different sources. Simply identifying and eradicating a common

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source of bacteria does not seem to be the total solution. On the other hand, ribotypes that appeared more than once seem to be less susceptible to antibiotics, and the mean MDR index of the 4 most common ribotypes was 2.86, compared with 3.92 for ribotypes which only occurred once. This could imply that multi-resistant Pseudomonas are more likely to persist as a selective advantage created by the specific antibiotic pressure. It is not difficult to imagine that antibiotic resistance confers some advantage to bacteria attempting to survive in the ICU environment. Identifying these persistent colonizers, which accounted for almost half of the isolates in this study, may indeed significantly decrease the incidence of nosocomial infections. Vigilance and the ability to identify specific strains, as was done in this study by ribotyping, will be key to accomplishing this task, for all ribotypes are not always evenly distributed over time and variation of susceptibility patterns within the same ribotype is possible, making phenotypic screening for hospital outbreaks useless. Ribotype 75, found in 6 patients, did not make its appearance until cycle 3 of the study, Ribotype 14 was seen during all cycles, but only colonized six patients; one during cycle 1, one in cycle 2, three in cycle 3 and one in cycle 4. Ribotype 40 was introduced during cycle 2 and remained present during the rest of the study. This ribotype had the worst susceptibility for ciprofloxacin and piperacillin-tazobactam, but only colonized three patients and was probably selected for during the different antibiotic regimens. During the first cycle ribotype 3 colonized four patients, three during the second cycle and was absent when ciprofloxacin was reintroduced in cycle 3 colonizing three different patients again. However, it reappeared in the last cycle in three patients again. Perhaps ribotypes 3 and 40 were present during the whole study, but escaped detection during the cycles they did not occur. Because the surveillance cultures were performed just for this study and ribotyping was performed at a later stage, results were not known in real time and detection was not possible at that time, because clonal spread was not detected from clinical isolates. We can only assume that factors other than antibiotic use, including breakdown in infection control were responsible for the spread of these ‘major clones’.

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The relationship of different ribotypes to the pattern of antibiotic use is difficult to establish.10 No consistent pattern emerged. Resistance to piperacillin-tazobactam fluctuated by cycle in the expected manner with more resistance occurring in times of greater beta-lactam use, but this was not seen with the quinolones. It is likely that other confounding variables exerted their influence at different times during the study. For example the average length of stay in the ICU (data not shown) progressively increased from cycle 1 to cycle 4, increasing the possibility of colonization by resistant strains during the latter stages of the study. The relatively high amount of quinolone use during off-cycles (cycles 2 and 4) may also have influenced the pattern of antimicrobial resistance. In addition the spread of one resistant clone will heavily influence the overall resistance of one intensive care unit and although there was no difference in infection control measures between the cycles, there may have been an undetected breakdown in hygiene. The data suggested that over the course of the entire study, higher antibiotic use correlated to higher antibiotic resistance (Figure 2), and higher resistance was seen with the more frequently occurring ribotypes, giving them a survival advantage and making them frequent colonizers in the ICU. Several lessons can be learned from this study. First, it is difficult to fully restrict certain antibiotics in a cycling rotation. Antibiotic resistance patterns of clinically significant isolates and patient factors such as drug allergies, severity of illness, and organ dysfunction can take precedence over clinical protocol. Second, multi-resistant bacteria may defeat the benefit of antibiotic cycling, retaining their survival advantage under successive cycling rotations. For example, up-regulation of an efflux system can be responsible for the simultaneously compromise of different antibiotic classes.11,12 Subsequently, these multi-resistant microbes are difficult to eliminate during a cycling study, because they were introduced in one cycle and, due to their multi-resistance, can persist during the following cycles when other antibiotics are used. Pseudomonas spp. are notorious for this characteristic and therefor may not be affected by cycling at all.13 Of our Pseudomonas isolates, 71 % were resistant to both ciprofloxacin and piperacillin-tazobactam, and 61% were resistant to

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three or more of the antibiotics tested. Our study showed a mixture of diverse ribotypes interspersed with some persistent clonal isolates. We would expect that infection control measures would be of paramount importance in dealing with persistent clones, while spontaneous mutation, implied by the large number of different ribotypes, might be more amenable to control by antibiotic cycling. It is unlikely that antibiotic cycling alone will solve the problem of antibiotic resistance among bacterial pathogens in the intensive care unit. This is likely to be true of any single intervention. Finally, we found that antibiotic-resistance of Pseudomonas aeruginosa isolates from surveillance cultures taken in the ICU were significantly different compared to hospital-wide resistance to the two antibiotics cycled during the study, piperacillin-tazobactam and ciprofloxacin. The correlation of resistance to amount of antibiotics used (Figure 2) is the likely explanation, although we did not collect data for antibiotic use in the rest of the hospital. Interestingly the resistance of clinical isolates was somewhere in between the resistance of ICU surveillance isolates and general hospital data. Other factors may need to be considered in bacteria which are associated with infection, not just colonization. Perhaps some measure of virulence is lost in certain highly resistant bacteria. In considering the clinical relevance of the relationship between antibiotic use and resistance, one must also account for the complexity of the interaction between pathogen and host.

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References 1. Fridkin SK. Increasing prevalence of antimicrobial resistance in

intensive care units. Crit Care Med 2001; 29(4 Suppl):N64-8. 2. Archibald L, Phillips L, Monnet D, McGowan JE Jr, Tenover F,

Gaynes R. Antimicrobial resistance in isolates from inpatients and outpatients in the United States: increasing importance of the intensive care unit. Clin Infect Dis 1997; 24:211-5.

3. McGowan JE Jr. Antimicrobial resistance in hospital organisms and its relation to antibiotic use. Rev Infect Dis 1983; 5:1033-48.

4. Rahal JJ, Urban C, Horn D, et al. Class restriction of cephalosporin use to control total cephalosporin resistance in nosocomial Klebsiella. JAMA1998; 280:1233-7.

5. Kollef MH. Is there a role for antibiotic cycling in the intensive care unit? Crit Care Med 2001; 29(4 Suppl):N135-42.

6. Pujol M, Gudiol F. Evidence for antibiotic cycling in control of resistance.Curr Opin Infect Dis 2001; 14:711-5.

7. Bukholm G, Tannaes T, Kjelsberg AB, Smith-Erichsen N. An outbreak of multidrug-resistant Pseudomonas aeruginosa associated with increased risk of patient death in an intensive care unit. Infect. Control Hosp Epidemiol 2002; 23:441–6.

8. Fagon, J Y, Chastre J, Domart Y, Trouillet JL, Gibert C. Mortality due to ventilator-associated pneumonia or colonization with Pseudomonas or Acinetobacter species: assessment by quantitative culture of samples obtained by a protected specimen brush. Clin Infect Dis 1996; 23:538–42.

9. Brisse S, Milatovic D, Fluit AC, et al. Molecular surveillance of European quinolone-resistant clinical isolates of Pseudomonas aeruginosa and Acinetobacter spp. using automated riboprinting. J Clin Microbiol 2000; 38:3636-45.

10. Monnet DL, Archibald LK, Phillips L, Tenover FC, McGowan JE Jr, Gaynes RP. Antimicrobial use and resistance in eight US hospitals: complexities of analysis and modeling. Intensive Care Antimicrobial Resistance Epidemiology Project and National Nosocomial Infections Surveillance System Hospitals. Infect Control Hosp Epidemiol 1998; 19:388-94.

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11. Levy SB. Active efflux, a common mechanism for biocide and antibiotic resistance. Symp Ser Soc Appl Microbiol 2002; 31(Supll 1):S65-S71.

12. Zgurskaya HI. Molecular analysis of efflux pump-based antibiotic resistance. Int J Med Microbiol 2002; 292:95-105.

13. Livermore DM. Multiple mechanisms of antimicrobial resistance in Pseudomonas aeruginosa: our worst nightmare? Clin Infect Dis 2002; 34:634-40.

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Genetic Determinants Involved in ß-Lactam- and Multiresistance

in a Surgical ICU.

H.J. van Loon, A.T.A. Box, J. Verhoef, A.C. Fluit

Published

International Journal of Antibiotic Agents 2004; 24:130-134

Chapter VIII

Abstract Antibiotic resistance is a major and well-known problem in intensive care units (ICUs) world-wide and previously susceptible isolates become resistant through the acquisition of resistance determinants from other bacteria or the development of mutations, as is the case in ß-lactam resistance. We evaluated the presence of resistance determinants (e.g. integrons) involved in ß-lactam resistance and multi-resistance in order to establish the contribution of horizontal gene transfer to the spread of resistance in a surgical ICU during an antibiotic rotation study. Pseudomonas aeruginosa and Enterobacteriaceae isolates were selected and iso-electric focusing (IEF), DNA-typing methods such as specific beta-lactamase and specific integron PCRs were performed to determine the presence of beta-lactamases. The PCRs specific for IMP-1, OXA-1, and VIM-type ß-lactamases performed on the selected P. aeruginosa and Enterobacteriaceae isolates with MICs for cephalosporins >1:g/ml yielded no evidence for these ß-lactamases. IEF for 14 pseudomonads, representing 7 genotypes from 9 patients from all cycles of the Cyclone trial, revealed the presence of a ß-lactamase with a pI larger than 8.5 in 13 of the isolates. The integrase PCR was positive for only 5 isolates from 3 patients and conserved segment PCR showed integrons of variable sizes (700, 900, 1400 and 1500 bp). Each patient had its own integron types. It can be concluded that integrons and associated resistance determinants played only a minor role in the surgical ICU and ß-lactam resistance among P. aeruginosa isolates was most likely due to the derepression of it�s AmpC gene.

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Genetic Determinants and Multiresistance

Introduction Antibiotic resistance is a major and well-known problem in intensive care units (ICUs) world-wide.1 Antibiotic-resistant bacteria in ICUs arise from different sources. For example, patients may already harbor a resistant microorganism on admission, which is subsequently selected by antibiotic usage, or resistant strains may be introduced by health care workers. In addition, previously susceptible isolates may also become resistant through the acquisition of resistance determinants from other bacteria or the development of mutations, as is the case in ß-lactam resistance. For the development of ß-lactam resistance the presence of a ß-lactamase encoding gene, which expresses the enzyme, is required. Genes encoding ß-lactamase enzymes are frequently located on plasmids. This property makes them exceptionally prone to spread by horizontal transfer, because many plasmids can be transferred from strain to strain by conjugation. The transfer of such a plasmid not only leads to e.g. ß-lactam antibiotic-resistance, but can also lead to multi-drug resistance when they carry multiple resistance genes. This horizontal transfer process can be very efficient and can occur at a frequency of 10-2 in vitro, which is only an indication for in vivo transfer, because in vivo frequencies are unknown.2 Chromosomally encoded genes are mobilized at much lower frequencies if at all. The development of resistance through mutations can also play an important role in the development of ß-lactam resistance in e.g. the genus Citrobacter, Enterobacter, and Pseudomonas. These genera possess a gene encoding for a chromosomally encoded ß-lactamase (AmpC), which is under the control of a repressor (Fig .1). Mutations in either the repressor or the repressor binding DNA sequence, may result in ineffective binding of the repressor and thereby control of expression resulting in constitutive expression of resistance.3 Four classes of ß-lactamases have been described.4,5 Class A has a serine at its active site, is generally plasmid encoded and constitutively expressed. This is the most commonly encountered class of the ß-lactamases. Class B enzymes have a zinc atom at their active center.

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promotor bla

sensor

β-lactam

Protection by ß-lactamdegradation

repressor

genes forsensor andrepressor

expression

ß-lactamase

Figure 1:Schematic representation of the regulation of AmpC ß-lactamases in, e.g., P. aeruginosa.

sulIqacEd1

IntI1

3' ConservedSegment

Orf5P1 P2

Pint

5' ConservedSegment

gene-cassette

59 be

P

59 be

P

AttI

PCR-primers

1 2935

Figure 2: Schematic representation of a class 1 integron. P1: promotor for trancription of gene cassettes; P2: second promotor that is usually inactive; int: integrase gene; attI1: integration site; 59-be: 59 base element recognized by the integrase; deltaqacE: partially deleted gene that encoded quarternary ammonium compound resistance; sulI: sulfonamide resistance; orf5: unknown function; P promotors of the deltaqacE and sulI genes, resp.

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These enzymes are capable of hydrolyzing carbapenems, which are very potent ß-lactam antibiotics. Resistance due to class B enzymes is sill uncommon, but is increasing.6 Class C enzymes are usually inducible, chromosomally encoded enzymes (AmpC). However, as noted above derepression and transfer to plasmids is an increasing phenomenon.7 Class D enzymes are currently only of minor importance. There is a strong association between multiresistance and the presence of integrons.8 Integrons are genetic elements that encode an integrase that is capable of inserting and excising gene cassettes from integrons (Fig. 2). Integrons consist of a 5'-conserved segment (CS) encoding the integrase and a promotor region for the gene cassettes (up to eight gene cassettes have been described) and a 3'-conserved segment. This latter segment contains usually a partially deleted gene encoding for quarternary ammonium compound resistance and resistance to sulfamethoxazole. However, the 3'-CS is less conserved than the 5'-CS. The gene cassettes consist of a coding sequence and a so-called 59 base element, which is a DNA sequence recognized by the integrase and necessary for integration and excision. More than 100 different gene cassettes have been described and at least 90% of them encode antibiotic resistance.9 This also includes resistance against carbapenems encoded by class B ß-lactamases. Strategies to reduce the prevalence of (multi)resistant organisms are drawing increased attention. Several intervention studies have shown that a change in antibiotic policy can lead to a reduction in the number of resistant isolates.10-16 Based on these observations an antibiotic cycling policy was instituted in our surgical ICU (Cyclone trial) during which antibiotic policies were rotated in 4 cycles of 4 months. The empiric antibiotics of choice during the four cycles were levofloxacin, cefpirome, levofloxacin, and piperacillin/tazobactam, respectively. A statistically significant decrease in the acquisition of levofloxacin-resistant gram-negative bacteria was observed after restriction of levofloxacin (p=0.011), but there was an increase after reintroduction of levofloxacin again (p=0.017).

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No significant changes were observed in the acquisition of cefpirome-resistant micro-organisms, whereas resistance to piperacillin/tazobactam showed only slight changes.17 The purpose of the present study was to evaluate the presence of resistance determinants (e.g. integrons) involved in ß-lactam resistance and multi-resistance, in order to establish the contribution of horizontal gene transfer to the spread of resistance during the Cyclone trial in the surgical ICU. Materials and methods Isolate selection During the Cyclone trial surveillance culture isolates were stored when they were resistant to fluoroquinolones, piperacillin/tazobactam, third-genereation cephalosporins, carbapenems or aminoglycosides. In addition, susceptible isolates from patients having a previously resistant isolate were also stored. P. aeruginosa isolates, the most frequently isolated microorganisms during the Cyclone trial, were ribotyped.18 Subsequently, isolates with identical ribotypes and unique susceptibility patterns were selected to analyze a build up of resistance determinants within a specific strain (a total of 69 isolates divided over 10 ribotypes). In addition ribotyped isolates of Enterobacteriaceae (E. cloacae, E. coli, K. oxytoca, K. pneumoniae; N=21), with unique antibiotic susceptibility patterns, from the same patients were also included to analyze the possibility of interspecies transfer of resistance determinants. ß-Lactamase-specific PCRs Specific PCRs for VIM-type, CTX-M-type, OXA-1, and IMP-1 ß-lactamases were performed. Because about 40% of the isolates were carbapenem-resistant we wanted to identify Pseudomonas specific ESBL�s with carbapenem hydrolyzing activity. The VIM-specific PCR was performed using primers as described by Poirel et al.19 PCR incubation started with 5 min 94°C followed by 35 cycles of 1 min

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94°C, 1 min 62°C and 1 min 72°C. The incubation mixtures consisted of 25 pmol of each primer, 25 nmol of each dNTP, 0.6 U SuperTaq DNA polymerase (HT Biotech, Cambridge, UK), and SuperTaq buffer in a total volume of 25 :l. The CTX-M-specific PCR was performed using primers 5�CGA TGT GCA GTA CCA GTA A- and 5'-ATA TCG TTG GTG GTG CC (bp 214-735 of the coding sequence; accession no. GenBank U95364). PCR incubation started with 5 min 94°C followed by 35 cycles of 1 min 94°C, 1 min 50°C, 1 min 72°C. The composition of the incubation mixtures was as described for the VIM-specific PCRs. The OXA-1-specific PCR was performed using primers 5'-ACA CAA TAC ATA TCA ACT TCG C and 5'-AGT GTG TTT AGA ATG GTG ATC (bp 133-926 of the coding sequence; Accession no. Genbank AJ28349). PCR incubation started with 5 min 96°C followed by 35 cycles of 1 min 96°C, 1 min 61°C and 1 min 72°C. The composition of the incubation mixtures was as described for the VIM-specific PCRs. The IMP-1-specific PCR was performed using primers 5'-GGC GTT TAT GTT CAT ACT TC and 5'-TCG AGA ATT AAG CCA CTCT TA (bp 97-330 of the coding sequence; accession no. Genbank: D50438). PCR incubation started with 5 min 94°C followed by 35 cycles of 1 min 94°C, 1 min 55°C and 45 sec 72°C. Composition of incubation was as described for the VIM-specific PCRs. Iso-electric focusing of ß-lactamases Iso-electric focusing (IEF) of ß-lactamases was performed on PhastgelTM IEF 3-9 gels (Amersham Pharmacia Biotech AB, Uppsala, Sweden) as described by the manufacturer. E. coli 539 with ß-lactamases TEM-1, SHV-2a and CTX-M-9 was used as a positive control (pI�s 5.4, 7.6, 8.0 resp.). ß-Lactamases were detected using nitrocefin (Oxoid, Basingstoke, Hampshire, UK) in 0.1 M NaH2PO4, 1mM EDTA (pH 7.0) as substrate. Incubations with nitrocefin were performed for 10 min at 37°C.

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Integron-specific PCRs The PCR for the detection of the class 1 integrons and the presence of gene cassettes have been described before.2,8

Results B-lactamases The PCRs specific for IMP-1, OXA-1, and VIM-type ß-lactamases performed on the selected P. aeruginosa and Enterobacteriaceae isolates with MICs for cephalosporins >1:g/ml yielded no evidence for these ß-lactamases. The CTX-M-specific PCR was positive for one Enterobacter cloacae, one Klebsiella oxytoca and two Klebsiella pneumoniae. One K. pneumoniae, the E. cloaca and the Klebsiella oxytoca were obtained from the same patient. None of the P. aeruginosa isolates yielded an amplification product. IEF for 14 pseudomonads with an MIC for cephalosportins >1:g/ml representing 7 genotypes from 9 patients revealed the presence of a ß-lactamase with a pI larger than 8.5 in 13 of the isolates. These ß-lactamases were present in Pseudomonas isolates from all cycles of the Cyclone trial. From the piperacillin/tazobactam cycle, when an increase of ß-lactam resistance was observed, Enterobacteriaceae and pseudomonads with a MIC for piperacillin/tazobactam > 2.0 were selected for IEF: four E. coli (different genotypes), one E. cloacae, one K. pneumoniae, one K. oxytoca and eight P. aeruginosa (5 genotypes). All Enterobacteriaceae except the E. cloacae strain and one P. aeruginosa contained a ß-lactamase with a pI of approximately 5.4.

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Integrons The integrase PCR was positive for five isolates from three patients (one P. aeruginosa, one K. pneumoniae, one K. oxytoca, and two Enterobacter cloacae, with different ribotypes). The CS-PCR on these isolates showed that each patient had his own type(s) (Table 1).

patient

species

size CS-PCR products in bp

1 P. aeruginosa 1400 2 E. cloacae 900 + 1400 3 E. cloacae 700 + 1500 K. oxytoca 700 + 1500 K. pneumoniae 700 + 1500

Table 1. Characteristics of integron-positive isolates.

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Discussion ICUs are considered the epicenter of antibiotic resistance in hospitals. It is not only the spread of epidemic clones that play an important role in the dissemination of resistance, but also the horizontal transfer of genetic elements that confer antibiotic resistance. Frequently, the isolates are multi-resistant or carry ß-lactamases with extended-spectrum activity. These include true Extended Spectrum Beta-Lactamases (ESBL) (e.g. TEM, SHV, OXA, and CTX-M family members), AmpC ß-lactamases, and metallo-ß-lactamases (e.g. VIM and IMP family members). The former two groups are well known and representatives of these groups were already present in our hospital during the mid-1990's.20 Recently, VIM and IMP metallo-ß-lactamases have been described in France and Italy.19,21-25 The genes encoding these ß-lactamases were present on integrons, which are highly predictive for multi-resistance.8

Analysis of ß-lactamases harbored by isolates obtained as part of the Cyclone trial showed that none of the isolates carried an IMP-1 or VIM metallo-ß-lactamase. However, CTX-M-type ß-lactamases were present in an Enterobacter cloacae and two different Kleibsiella species from one patient. The presence of this ß-lactamase in three species is suggestive for horizontal transfer of this gene. But ESBLs do not seem to play a major role in resistance to ß-lactam antibiotics during the Cyclone trial. IEF of ß-lactamases from Pseudomonas isolates frequently showed the presence of an enzyme with a pI of ≥ 8.5, which is indicative of the chromosomally encoded AmpC of P. aeruginosa.2 This gene is under the control of a repressor (Fig .1). This repressor blocks transcription and hence the expression of the ß-lactamase. Only removal of the repressor leads to expression. Removal of the repressor is under the control of a sensor protein present in the cell membrane. Activation of the sensor leads to removal of the repressor. The sensor may be activated by a variety of different ß-lactam antibiotics, but usually not all. Ironically some ß-lactams may be good activators of the sensor, but poor substrates for the ß-lactamase, but other ß-lactam antibiotics may be poor activators and good substrates. Mutations in either the repressor or the repressor

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binding DNA sequence, which controls transcription may result in ineffective binding of the repressor and thereby control of expression resulting in constitutive expression of resistance. In this case resistance against ß-lactam antibiotics, which are poor inducers, but good ß-lactamase substrates will emerge. The IEF data combined with the MIC data (not shown) indicate that the AmpC gene is derepressed in many of the ß-lactam-resistant P. aeruginosa isolates.26 The common ß-lactamase found in the Enterobacteriaceae and one P. aeruginosa strain from the piperacillin/tazobactam cycle of the Cyclone trial, when an increase in piperacillin/tazobactam-resistance was observed, was probably a TEM- ß-lactamase.17 Among the Enterobacteriaceae and pseudomonads only a few integron-positive isolates were found. Each of the three patients with integron-positive isolates had its� own integron-type. Only one patient had multiple species and strains with the same integron. These were also the CTX-M-positive isolates. This further bolsters the case for horizontal transfer of resistance determinants among species in this patient. It can be concluded that integrons and associated resistance determinants played only a minor role during the Cyclone trial and ß-lactam resistance among P. aeruginosa isolates was most likely due to the derepression of its� AmpC gene. Whether an elevation of TEM- ß-lactamases took place during the piperacillin/tazobactam cycle of the Cyclone still remains to be investigated.

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References 1. Hanberger H, Diekema D, Fluit A, Jones R, Struelens M, and

Spencer R. Surveillance of antibiotic resistance in European ICUs. J Hosp Infect 2001; 48:161-76.

2. Leverstein-van Hall MA, Box ATA, Blok HEM, Paauw A, Fluit AC, Verhoef J. Evidence of extensive interspecies transfer of integron-mediated antimicrobial resistance genes among multidrug-resistant Enterobacteriaceae in a clinical setting. J Infect Dis 2002; 186:49-56.

3. Livermore DM. ß-Lactamases in laboratory and clinical resistance. Clin Microbiol Rev 1995; 8:557-84.

4. Schmitz FJ, Fluit AC. Mechanisms of resistance. In: Armstrong D, Cohen J (eds) Infectious Diseases. Harcourt Publishers Ltd 1999. Section 7 Chapter 2 pp1-14.

5. Majiduddin FK, Materon IC, Patzkill TG. Molecular analysis of beta-lactamase structures and function. Int J Med Microbiol 2002; 292:127-37.

6. Livermore DM, and Woodford N. Carbapenemases: a problem in waiting? Curr Opin Microbiol 2000; 3:489-95.

7. Barlow M, Hall BG. Origin and evolution of the AmpC β-lactamases of Citrobacter freundii. Antimicrob Agents Chemother 2002; 46:1190-8.

8. Leverstein-van Hall MA, Blok HEM , Donders AR, Paauw A, Fluit AC, and Verhoef J. 2003. Multidrug resistance among Enterobacteriaceae is strongly associated with the presence of integrons and is independent of species or isolate origin. J Infect Dis. 187:251-259.

9. Fluit AC, and Schmitz FJ. Class 1 integrons: gene cassettes, and epidemiology. Eur J Clin Microbiol Infect Dis 1999;18:761-70.

10. Leverstein -van Hall MA, Fluit AC, Blok HEM, et al. Control of nosocomial multiresistant Enterobacteriaceae using a temporary restrictive antibiotic agent policy. Eur J Clin Microbiol Infect Dis 2001; 20:785-91.

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11. Gerding DN, Larson TA, Hughes RA, et al. Aminoglycoside resistance and aminoglycoside usage: ten years of expirience in one hospital. Antimicrob Agents Chemother 1991; 35:1284-90.

12. Kollef MH, Vlaskin J, Sharpless L, et al. Scheduled changes of antibiotic classes. A strategy to decrease the incidence of ventilator-associated pneumonia. Am J Respir Crit Care Med 1997; 156:1040-8.

13. Dominguez EA, Smith TL, Reed E, et al. A pilot study of atibiotic cycling in a hematology-oncology unit. Infect Control Hosp Epidemiol 2000; 21(Suppl.):S4-S8.

14. de Man P, Verhoeven BAN, Verburgh HA, Vos MC, van den Anker. An antibiotic policy to prevent emergence of resistant bacilli. Lancet 2000; 355:973-8.

15. Gruson D, Hilbert G, Vargas F, et al. Rotation of antibiotics in a medical intensive care unit. Am J Resp Care Med 2000; 162:837-43.

16. Raymond DP, Pelletier SJ, Crabtree TD, et al. Impact of rotating empiric antibiotic schedule on infectious mortality in an intensive care unit. Crit Care Med 2001; 29: 1101-8.

17. van Loon HJ, Vriens MR, Fluit AC, et al. Antibiotic rotation and gram-negative resistance: the cyclone trial. Data in preparation of publication.(Chapter 4 of this thesis)

18. van Loon HJ, Leverstein-van Hall MA, Fluit AC, et al. Cross-transmission of microorganisms on a surgical ICU. Data in preparation of publication.(Chapter 5 of this thesis)

19. Poirel L, Naas T, Nicolas D, Collet L, Bellais S, Cavallo JD, and Nordmann P. Characterization of VIM-2, a carpanem-hydrolyzing metallo-ß-lactamase and its plasmid- and integron-borne gene from a Pseudomonas aeruginosa clinical isolate in France. Antimicrob Agents Chemother 2000; 44:891-97.

20. Leverstein- van Hall MA. The growing problem of drug resistant bacteria: the role of horizontal gene transfer. Academic thesis University of Utrecht, Utrecht, The Netherlands, 2002; ISBN 90-393-3144-8.

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21. Adams H, Teertstra W, Koster M, and Tommassen J. PspE (phage-shock protein E) of Escherichia coli is a rhodanese. FEBS Letters 2002; 518:173-76.

22. Laraki,N., Galleni,M., Thamm,I., Riccio,M.L., Amicosante,G., Frere,J.M. and Rossolini,G.M. Structure of In31, a blaIMP-containing Pseudomonas aeruginosa integron phyletically related to In5, which carries an unusual array of gene cassettes Antimicrob Agents Chemother 1999; 43:890-901.

23. Poirel L, Lambert T, Turkoglu S, Ronco E, Gaillard J, Nordmann P. Characterization of Class 1 integrons from Pseudomonas aeruginosa that contain the bla(VIM-2) carbapenem-hydrolyzing beta-lactamase gene and of two novel aminoglycoside resistance gene cassettes. Antimicrob Agents Chemother. 2001 ; 45: 546-52.

24. Pallecchi L, Riccio ML, Docquier JD, Fontana R, Rossolini GM. Molecular heterogeneity of bla(VIM-2)-containing integrons from Pseudomonas aeruginosa plasmids encoding the VIM-2 metallo-beta-lactamase. FEMS Microbiol Lett. 2001; 195:145-50.

25. Lombardi G, Luzzaro F, Docquier JD, Riccio ML, Perilli M, Coli A, Amicosante G, Rossolini GM, Toniolo A. Nosocomial infections caused by multidrug-resistant isolates of Pseudomonas putida producing VIM-1 metallo-beta-lactamase. J Clin Microbiol. 2002; 40: 4051-5.

26. http://www.lahey.org/studies/webt.asp?D=http://www.lahey.org/studies/webt.htm&C=404

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Summary and general discussion

Chapter IX

Antibiotic resistance has reached pandemic proportions and the increasing incidences have alarmed medical healthcare associations world wide.1 Some thirty years ago it was almost all infectious diseases were conquered, but over the last decades we have witnessed the re-emergence of known contagious diseases and the emergence of new infections.2 This is partly due to the major increase in multi-resistant microorganisms, which have made infectious diseases more difficult to treat and have taken them back into focus of medical attention. Currently we are at severe risk of entering a post-antibiotic era with multi-drug resistant microorganisms increasing in numbers and only few new antibiotics in the pipe line of the pharmaceutical industry.3,4 This means that we must be prudent in the use of the remaining effective antimicrobial agents that are currently at our disposal. The aim of this thesis was to gain more insight in the feasibility and the effect of changes in antibiotic policy on antimicrobial resistance in a surgical ICU by answering the questions formulated in the introduction: 1. Is it possible to influence the antimicrobial treatment duration

in patients undergoing open management of the abdomen (OMA) in order to reduce excessive and unnecessary antibiotic utilization ?

In selected cases, open management of the abdomen (OMA) is the treatment of choice for persisting secondary peritonitis.5,6 Although the therapeutic value of antibiotics is clear, in patients with an established intraabdominal infection, there is still little consensus on the duration of the antimicrobial treatment.7-9 The aim of the randomized clinical trial, described in chapter II, was to assess the effectiveness of short compared to prolonged administration of antibiotics in patients undergoing OMA. We randomized patients to receive either five days or a minimum of eight days of antibiotic treatment. We observed recurrence of abdominal sepsis in four

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Summary & General Discussion

patients from the short group (A) and nine patients from the group (B) with prolonged antibiotics. There were no differences in clinical parameters between the groups, indicating ongoing sepsis or complications, while the prolonged group had a longer hospital stay (P=0.02). Because many patients still had life threatening conditions during their course of treatment, which warranted prolonged use of their antibiotics, we were unable to create two exactly comparable groups with a significant difference in duration of antibiotic treatment. This shows how difficult it is to enforce short antibiotic treatment in patients undergoing OMA. However, it is our opinion that short antibiotic treatment is in any case as effective as prolonged treatment and the duration of antibiotic treatment should be tailored for each individual patient. In view of these results and the known adverse effects as toxicity, antimicrobial resistance and high antibiotic costs, reducing antibiotic therapy in patients undergoing OMA to in principle 5 days will be a worthwhile aim, although the question remains if this is feasible in daily practice. 2. Can we create an objective model to determine outcome and a

guideline as to when antimicrobial treatment can be safely stopped in patients undergoing OMA ?

Adult Physiology and Chronic Health Evaluation II (APACHE II) and the Mannheimer Peritonitis Index (MPI) have been used to predict outcome in patients with secondary peritonitis.10 In chapter III we externally validated the Predictor Recurrence Abdominal Sepsis Open Management-score (PRASOM-score) and evaluated individual prognostic values in patients with severe secondary peritonitis undergoing OMA. We observed positive predictive values for the recurrence of abdominal sepsis from the day antibiotic treatment was discontinued when PRASOM-score was higher compared to patients with a low PRASOM-score and the predictive values of APACHE-II and MPI were also confirmed. The individual predictive variables, derived from the multivariate analysis of this study, showed better

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predictive values than existing scoring systems (e.g. blood albumin level), but they were derived from a small dataset and will have to be validated in a larger patient population. 3. Does antibiotic cycling change antimicrobial resistance levels in

a surgical ICU ? The increase in multi-resistant microorganisms, both gram-positive and Gram-negative, is an alarming phenomenon, especially for intensive care patients.11-13 There are three primary strategies to reduce the emergence and spread of antimicrobial resistance. The first consists of increased attention for infection control measures.14-16 The second strategy is good antibiotic stewardship, meaning the use of appropriate antimicrobial agents on good indications, at the right dosage and for a sufficient duration of time.17-21 The third strategy contains antibiotic-control programs such as formularies and education, combination antibiotic treatment, restriction programs and the cycling of antimicrobial agents.15,22-26 In order to attain a better understanding on the epidemiology of antibiotic resistance in Gram-negative microorganisms, we performed a prospective study in which two different antibiotic classes (quinolones and beta-lactam antibiotics), with different mechanisms for resistance development were cycled during four 4-month periods in a surgical ICU. Colonization with antibiotic-resistant Gram-negative bacteria was determined with intensive surveillance and bacterial genotyping was used to identify different acquisition routes. Cycling of quinolones with beta-lactams, as described in chapter IV, showed clear effects. The main features of this study are (a) that, despite 96% compliance with protocol, cycling with quinolones and beta-lactam antibiotics only modified 27% to 49% of the overall antibiotic use, that (b) the use of both quinolones and piperacillin-tazobactam were associated with increased acquisition of resistance, and that (c) total antibiotic use increased with 24% during the period of the study. These findings demonstrate that cycling of homogeneous antibiotic exposure (i.e., repeated rotation of two antibiotic classes) is

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associated with changing profiles of resistance development, which questions its use as a strategy to prevent antibiotic resistance in ICUs. Improving infection prevention and reducing antibiotic use probably are the only meaningful strategies to control antibiotic resistance. 4. What is the additional value of the routine typing of potential

pathogens from surveillance cultures taken in the ICU ? In chapter V we performed DNA-fingerprinting of Gram-negative and Staphylococcus aureus isolates from prospectively collected surveillance cultures, during the Cyclone trial described in chapter IV, to evaluate the magnitude of otherwise unknown cross-transmission in our surgical ICU. The results of genotyping of the routine surveillance cultures brought to light five major epidemics; one with Acinetobacter calcoaceticus involving four patients, one with Enterobacter cloacae involving 10 patients, two with Pseudomonas aeruginosa involving eight and 13 patients, and one with MSSA involving eight patients. In chapter VI the spread of an epidemic Enterobacter cloacae clone is described, which escaped the conventional phenotypically based hospital surveillance systems for epidemic spread, because of its 28 different antibiotic susceptibility patterns. Furthermore, this chapter demonstrated that enhanced infection prevention measures concerning patients colonized with the specific clone were not enough to stop its spread and illustrates that the spread of bacteria occurs almost on a daily basis. Both chapter V and chapter VI question the effectiveness of the current detection systems based primary on phenotypic characteristics. A more prominent role for genotyping in first-line screening seems to offer significant advantages in our battle against the bugs.

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5. What is the impact of antibiotic rotation in a United States medical ICU on Pseudomonas aeruginosa ?

One of the major pathogens causing ICU infections is the Pseudomonas aeruginosa.27,28 This Gram-negative rod was the most frequently recovered microorganism from surveillance cultures during the American equivalent of the Dutch Cyclone trial, called the RADAR (Rotating Antibiotics to Decrease Antimicrobial Resistance) study. The aim of the study as described in chapter VII was to examine the evolution of antibiotic-resistance and spread of Pseudomonas aeruginosa during a rotational antibiotic policy in a United States medical ICU. Twenty-eight different ribotypes were found among 82 Pseudomonas isolates, 13 ribotypes were unique and occurred in only one patient. Four ribotypes accounted for 42 (51%) isolates and were designated the �major clones� occurring throughout multiple cycles. The ribotypes with multiple occurrences expressed more resistance to antibiotics than ribotypes which appeared only once. The correlation of antibiotic use with antibiotic resistance and the finding of a large number of different ribotypes found in Pseudomonas aeruginosa, suggests that de novo development of antibiotic resistance is a likely event in Pseudomonas aeruginosa. In addition, ribotypes associated with antibiotic resistance appear to have a survival advantage and can become frequent colonizers in the ICU. 6. Can we relate changes in antibiotic resistance levels to (inter-

species) transfer of resistance genes ? In chapter VIII we evaluated the presence of resistance determinants (e.g. integrons) involved in ß-lactam resistance and multi-resistance in a surgical ICU, to establish the contribution of horizontal gene transfer to the spread of resistance during the Cyclone trial. Analysis of ß-lactamases in isolates obtained as part of the Cyclone trial demonstrated that ESBLs did not play a major role in resistance to ß-lactam antibiotics and that ß-lactamases from Pseudomonas isolates frequently showed the presence of an enzyme indicative of the

172


chromosomally encoded AmpC of Pseudomonas aeruginosa.29 It appeared that there was hardly any influence or contribution from horizontal gene transfer in the (interspecies) spread of resistant determinants and the spread of possible pathogenic microorganisms from patient to patient. This thesis has demonstrated that changes in antibiotic policies actually have a relevant effect on antimicrobial resistance levels and that the length of antibiotic treatment should continuously be weighed. Alternating antibiotic policies alone will not be effective enough. A good interplay with other factors such as good antibiotic stewardship, increased infection control measures and an active surveillance system (based on phenotypic susceptibility patterns in combination with DNA-fingerprints) will be needed to place future colonization rates with (multi-) resistant microorganisms into perspective. The potential hazard of the coming decades will be the increasing frequencies of interspecies gene transfer, with the transfer of the vanA gene from the Enterococcus spp. to Staphylococcus aureus, rendering the Staphylococcus aureus vancomycin resistant, only as the beginning.30

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References 1. Low DE, Kellner JD, Wright GD. Superbugs: How they evolve

and minimize the cost of resistance. Curr Infect Dis Rep1999; 1:464-9.

2. Pollard AJ, Dobson SR. Emerging infectious diseases in the 21st century. Curr Opin Infect Dis 2000; 13:265-75.

3. Cohen ML. Changing patterns of infectious disease. Nature 2000; 406:762-7.

4. McGowan JE jr. Economic impact of antimicrobial resistance. Emerg Infect Dis 2001; 7:286-92.

5. Schein M. Surgical management of intra-abdominal infection: is there any evidence. Langenbecks Arch Surg 2002; 387: 1-7.

6. Bosscha K, van Vroonhoven JMV, van der Werken Chr. Surgical management of severe secondary peritonitis. Br J Surg 1999; 86: 1371-7.

7. Dellinger EP. Undesired effects of antibiotics and future studies. Eur J Surg Suppl 1996; 576: 29-32.

8. Bohen JMA. Postoperative peritonitis. Eur J Surg Suppl 1996; 576: 50-2.

9. Alcocer F, Lopez E, Calva JJ, Herrera MF. Antibiotic treatment in secondary peritonitis: towards a defenition of its optimal duration. Rev Invest Clin 2001; 53: 121-5.

10. Bosscha K, Reijnders K, Hulstaert PF, et al. Prognostic scoring systems to predict outcome in peritonitis and intra-abdominal sepsis. Br J Surg 1997; 84:1532-4.

11. McGowan JE Jr. Increasing threat of gram-positive bacterial infections in the intensive care unit setting. Crit Care Med 2001; 29(Suppl 4):N69-N74.

12. Kollef MH, Fraser VJ. Antibiotic resistance in the intensive care unit. Ann Int Med 2001; 134:298-314.

13. Hanberger H, Diekema D, Fluit A, et al. Surveillance of antibiotic resistance in European ICU�s. J Hosp Infect 2001; 48:161-176.

14. Teare L, Cookson B, Stone S. Hand hygiene. Use of alcohol hand rubs between patients:they reduce the transmission of infection. BMJ 2001; 323:411-412.

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15. Weinstein RA. Controlling antimicrobial resistance in hospitals: infection control and use of antibiotics. Emerg Infect Dis 2001; 7:188-192.

16. Puzniak LA, Leet T, Mayfield J, Kollef M, Mundy LM. To gown or not to gown: the effect on acquisition of vancomycin-resistant enterococci. CID 2002; 35:18-25.


18. Singer MV, Haft R, Barlam T, et al. Vancomycin control measures at a tertiary-care hospital: impact of interventions on volume and patterns of use. Infect Control Hosp Epidemiol 1998; 19:248-253.

19. Gerding DN. Good antimicrobial stewardship in the hospital: fitting, but flagrantly flagging. Infect Control Hosp Epidemiol 2000; 21:253-255.

20. Bell DM. Promoting appropriate antimicrobial drug use: perspective from the centers for disease control and prevention. CID 2001; 33(Suppl 3):S245-S250.

21. Fridkin SK, Lawton R, Edwards JR, et al. Monitoring antimicrobial use and resistance: comparison with a national benchmark on reducing vancomycin use and vancomycin- resistant enterococci. Emerg Infect Dis 2002; 8:702-707.

22. Shlaes DM, Gerding DN, John JF Jr, et al. Society for healthcare epidemiology of America and infectious diseases society of America joint committee on the prevention of antimicrobial resistance: guidelines for the prevention of antimicrobial resistance in hospitals. CID 1997; 25:584-599.

23. Rice LB. Successful interventions for Gram-negative resistance to extended-spectrum β-lactam antibiotics. Pharmacotherapy 1999; 19(8 Pt 2):120S-128S.

24. Smith DW. Decreased antimicrobial resistance following changes in antibiotic use. Surg Infect 2000; 1:73-78.

25. Murthy R. Implementation of strategies to control antimicrobial resistance. Chest 2001; 119:405S-411S.

26. Allegranzi B, Luzzati R, Luzzani A, et al. Impact of antibiotic changes in empirical therapy on antimicrobial resistance in

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intensive care unit-acquired infections. J Hosp Infect 2002; 52:136-140.

27. Bukholm G, Tannaes T, Kjelsberg AB, Smith-Erichsen N. An outbreak of multidrug-resistant Pseudomonas aeruginosa associated with increased risk of patient death in an intensive care unit. Infect. Control Hosp Epidemiol 2002; 23:441�6.

28. Fagon, J Y, Chastre J, Domart Y, Trouillet JL, Gibert C. Mortality due to ventilator-associated pneumonia or colonization with Pseudomonas or Acinetobacter species: assessment by quantitative culture of samples obtained by a protected specimen brush. Clin Infect Dis 1996; 23:538�42.

29. M.A.Leverstein-van Hall, A.T.A. Box, H.E.M. Blok, A. Paauw, A.C. Fluit, J. Verhoef. 2002. Evidence of extensive interspecies transfer of integron-mediated antimicrobial resistance genes among multidrug-resistant Enterobacteriaceae in a clinical setting. J. Infect. Dis. 186: 49-56.

30. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5126a1.htm

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Chapter X

Summary in Dutch

Samenvatting in het Nederlands

Chapter X

Antimicrobiële resistentie heeft pandemische proporties bereikt en is een alarmerend teken voor medische gezondheids instellingen wereld wijd. Ongeveer dertig jaar geleden, na de introductie van breed-spectrum antibiotica, dacht men dat zo goed als alle infectie ziekten onder controle waren, echter de laatste decennia hebben toch weer bekende en onbekende infectie ziekten de kop opgestoken. Door de toename van multi-resistente microorganismen zijn de huidige infectie ziekten moeilijker te behandelen, omdat er steeds minder pathogene microorganismen gevoelig zijn voor de huidige antibiotica. Door het achterblijven van nieuwe ontwikkelingen in de farmaceutische industrie ontstaat zelfs het gevaar van een post-antibiotisch tijdperk. Het moge duidelijk zijn dat er dus zuinig en verstandig omgegaan dient te worden met de antibiotica die we nog tot de beschikking hebben. Het doel van dit proefschrift was een beter inzicht te verschaffen in de mogelijkheden en de effecten van veranderingen in antibioticum beleid op antimicrobiële resistentie. Dit werd onderzocht door antwoord te verschaffen op de volgende vragen: 1. Is het mogelijk de antibiotische behandelingsduur te

beinvloeden van mensen die een open buik behandeling ondergaan ?

In geselecteerde gevallen van persisterende secundaire peritonitis is men aangewezen op een open buik behandeling (OBB). De waarde van antibiotica bij deze behandeling staat vast, echter er is nog steeds geen consensus over de antibiotische behandelingsduur voor patiënten met een gemanifesteerde intra-abdominale infectie. Het doel van de prospectief gerandomizeerde studie, beschreven in hoofdstuk II, was om de effectiviteit van korte danwel langdurige antibiotica toediening te vergelijken in patiënten die een OBB ondergingen. Patiënten werden gerandomizeerd om; of kort (vijf dagen), of om langdurig (minimaal acht dagen) antibiotica toegedient te krijgen. Recidief abdominale sepsis werd waargenomen in vier patiënten van de korte groep en in negen patiënten van de langdurige

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Summary in Dutch

groep. Er werden geen verschillen waargenomen in klinische parameters die konden wijzen op persisterende sepsis of complicaties. De langdurige groep had een langere opname duur (P=0.02). Veel patiënten in de korte groep waren dermate ziek waardoor het on-ethisch was voortijdig (op dag 5) hun antibiotica te staken. Hierdoor bleek het niet mogelijk twee exact verschillende groepen met betrekking tot de antibiotische behandelingsduur te creëren. Echter, ons inziens volgt uit de data wel gelijke effectivitiet van korte danwel langdurige antibiotica toediening en zou per individuele patient een behandeling op maat moeten plaats vinden. Daarom pleiten wij voor correct antibiotica gebruik, dat wil zeggen op de juiste indicatie het juiste middel en de behandelingsduur afstemmen per individuele patiënt. Hierdoor kunnen hopelijk bijwerkingen als toxiciteit, antimicrobiële resistentie en hoge kosten worden beperkt en een behandelingsduur van 5 dagen worden nagestreefd, hoewel het de vraag blijft of dit haalbaar zal zijn in de dagelijkse praktijk. 2. Is het mogelijk een objectief model te creëren om te fungeren

als leidraad voor de duur van antibiotische behandeling in OBB patiënten ?

De Acute Physiology and Chronic Health Evaluation II (APACHE II) en de Mannheimer Peritonitis Index (MPI) zijn score systemen die worden gebruikt om mortaliteit te voorspellen in patiënten met een secundaire peritonitis. In hoofdstuk III hebben we een eerder gecreerde score, de Predictor Recurrence Abdominal Sepsis Open Management-score (PRASOM-score), extern gevalideerd en werden individueel voorspellende factoren geevalueerd in patiënten met secundaire peritonitis die een OBB ondergingen. Op de dag dat antibiotica werden gestaakt waren hogere PRASOM-scores gerelateerd aan een hogere frequentie van recidief abdominale sepsis. Dit werd ook bevestigd voor de APACHE II en MPI. De individueel voorspellende variabelen, verkregen uit het multivariable model van de studie (b.v. bloed albumine), lieten een betere voorspellende waarde zien voor recidief en mortaliteit dan de

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bestaande scorings systemen. Hogere scores op de dag dat antibiotica gestaakt werden zouden er op kunnen duiden dat de antibiotica, in de desbetreffende patiënt, nog niet gestaakt dienen te worden. Echter, waar de �cut-off� score ligt is nog niet duidelijk en moeten de nieuwe modellen in een grotere studie populatie gevalideerd worden. 3. Verandert het cyclisch geven van antibiotica het antimicrobiële

resistentie niveau op een chirurgische ICU ? De toename van multi-resistente microorganismen, Gram-positief en Gram-negatief, is een alarmerend fenomeen, met name voor intensive care patiënten. Er zijn drie hoofd strategiën om het ontstaan en de verspreiding van antimicrobiële resistentie te reduceren. De eerste bestaat uit een toename van infectie preventie maatregelen. De tweede uit correct antibiotica gebruik, dat wil zeggen; het juiste middel voor de juiste indicatie, in de juiste dosering en de juiste duur van behandeling. De derde strategie bestaat uit antibiotica controle programma�s zoals, formularia en onderwijs, combinatie antibiotica therapie, restrictie programma�s en cyclisch antibiotica beleid. Om een beter inzicht te verschaffen in het concept van cyclisch antibiotica beleid en de impact ervan op resistentie van Gram-negatieve microorganismen hebben we de behandeling van twee verschillende klassen antibiotica (quinolon en beta-lactam) met elkaar afgewisseld, gedurende vaste perioden, op een chirurgische intensive care (hoofdstuk IV). Het cyclische gebruik van quinolon en beta-lactam antibiotica toonde duidelijke effecten. De hoofduitkomsten lieten zien dat (a) ondanks een protocol compliance van 96% het cyclisch geven van quinolon en beta-lactam antibiotica het totaal antibiotica gebruik slechts 27 %-49% beinvloedde, (b) het gebruik van quinolonen en piperacilline-tazobactam beide geassocieerd waren met verhoogde acquisitie van kolonizatie met antibiotisch-resistente microorganismen, en (c) het totaal antibiotica gebruik gedurende de studie met 24% was gestegen. Deze bevindingen geven aan dat het cyclisch gebruik van homogene antibiotische blootstelling (b.v. cyclisch gebruik van twee

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antibiotische classen) gepaard gaat met verschillende profielen van antibiotische resistentie ontwikkeling, waardoor deze strategie zijn eigen nut tot het beperken van antibiotica resistentie in de intensive care beperkt. Het verbeteren van infectie preventie en het verminderen van antibiotica gebruik lijken vooralsnog de enige strategieën van betekenis om antibiotica resistentie het hoofd te bieden. 4. Wat is de waarde van het routinematig typeren van potentieel

pathogene microorganismen uit surveillance kweken van een intesive care unit ?

In hoofdstuk V werd DNA-identificatie van Gram-negatieve microorganismen en Staphylococcus aureus verricht van prospectief verzamelde isolaten gedurende de Cyclone trial (hoofdstuk IV) om te bestuderen in welke mate er sprake was van onbekende kruis-transmissie van microorganismen tussen verschillende patiënten. De studie bracht vijf �major� epidemieën aan het licht: één met Acinetobacter calcoaceticus (vier patiënten), één met Enterobacter cloacae (10 patiënten), twee met Pseudomonas aeruginosa (8 en 13 patiënten) en één met MSSA (acht patiënten). In hoofdstuk VI werd de verspreiding van een epidemische Enterobacter cloacae kloon beschreven, die waarschijnlijk door het bezit van 28 verschillende fenotypen (resistentie patronen) aan het ziekenhuis surveillance systeem wist te ontkomen. Toegenomen infectie preventie maatregelen konden de verspreiding niet stuiten en bacteriële verspreiding bleek een bijna dagelijks fenomeen. Hoofdstuk V en VI zetten beide een groot vraagteken achter de huidige detectie systemen voor epidemische verspreiding die primair zijn gebaseerd op fenotypische karakteristieken van de verschillende microorganismen en pleiten beiden voor detectie systemen waarin genotypring een prominetere rol krijgt.

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5. Welke impact heeft een cyclisch antibioticum beleid op Pseudomonas aeruginosa, in een United States medische ICU ?

Pseudomonas aeruginosa is één van de meest voorkomende verwekkers van ziekenhuis gerelateerde infecties. In de RADAR-trial, het Amerikaanse equivalent van de Cyclone trial (hoofdstuk IV), was de Pseudomonas het meest gekweekte microorganisme. Het doel van deze studie, zoals beschreven in hoofdstuk VII, was de ontwikkeling en de verspreiding van antibioticum resistente pseudomonaden te bestuderen gedurende een roterend antibioticum beleid op een medische intensive care. Er werden 28 verschillende ribotypes geïdentificeerd uit 82 Pseudomonas isolaten. 13 ribotypes waren uniek en behoorden allen toe aan individuele patiënten. Vier ribotypes besloegen 42/82 van de isolaten en werden �major clones� genoemd, die in meerdere cycli voorkwamen. De isolaten met een ribotype dat vaker voorkwam gedurende verschillende cycli toonden uitgebreidere resistentie patronen in vergelijking met de isolaten die uniek waren. Het verband tussen antibioticum gebruik en resistentie, en het grote aantal verschillende ribotypen is suggestief voor het �de novo� ontstaan van resistentie in Pseudomonas aeruginosa. Daarnaast hebben de resistente isolaten een overlevings voordeel bij veelvuldig breed-spectrum antibiotica gebruik en maakt hen tot frequente colonizatoren van intensive care units. 6. Kunnen veranderingen in het antimicrobiële resistentie niveau

worden gerelateerd aan (inter-species) overdracht van resistentie genen ?

In hoofdstuk VIII hebben we de aanwezigheid van resistentie determinanten zoals integronen, betrokken bij β-lactam resistentie en multi-resistentie, in kaart gebracht om de bijdrage van �horizontal gene transfer� aan de verspreiding van resistentie te bestuderen. Analyse van β-lactamases in isolaten verzameld gedurende de Cyclone trial wezen uit dat ESBLs geen grote rol speelden in β-lactam antibiotica resistentie. In Pseudomonas isolaten werden frequent β-

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lactameses waargenomen die een enzym bevatten dat indicatief was voor het chromosomaal gecodeerde AmpC van Pseudomonas aeruginosa. Er bleek geen sprake van een bijdrage van �horizontal gene transfer� aan de (interspecies) verspreiding van resistentie determinanten en de verspreiding van mogelijk pathogene microorgansimen van patiënt naar patiënt. Dit proefschrift heeft gedemonstreerd dat veranderingen in antibiotisch beleid een verandering in antibiotisch resistentie niveau teweeg brengt en dat de behandelingsduur met antibiotica continu gemonitord dient te worden. Alleen het aanpassen of alterneren van verschillende antibiotische beleiden zal niet volstaan. Een goed samenspel met factoren zoals, correct antibioticum gebruik, toegenomen infectie preventie maatregelen en een verscherpt detectie systeem voor epidemische verspreiding zullen noodzakelijk zijn om toekomstige kolonizatie met (multi-) resistente microorganismen in perspectief te houden. De komende decennia zal toename van interspecies resistentie-gen-overdracht potentiële gevaren opleveren, waarvan de overdracht van het vanA gen uit een Enterococcus spp. naar een Staphylococcus aureus die daardoor vancomycine-resistent wordt, slechts het begin is.

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&

Curriculum Vitae Auctoris

Acknowledgements

The research described in this thesis was not the single effort of one author. It was accomplished with the support of many people, who were indispensable for the realization of this dissertation. I would like to acknowledge them in full for their support, comments, discussions, time and energy. Prof. Dr Chr. van der Werken and Prof. Dr J. Verhoef, promotores of this thesis. Dear Sirs, I would very much like to thank you both for the continuous support, trust and guidance I received. You both kept my drive and focus going and I am proud that I was given the opportunity to grow and evolve under both your wings. Dr A.C. Fluit, co-promotor of this thesis. Dear Ad, thank you for your guidance and help performing experiments in the field of molecular biology. You opened a new door for me and took me by the hand. All experiments described in this thesis were thanks to your creative thoughts and experience. Dr M.R. Vriens. Menno, thank you for all the hard work you performed for the set-up and start-up of the CYCLONE-trial. You paved the way. Prof. Dr M.J.M. Bonten. Marc, thank you for the commitment and effort you put in helping me analyzing and editing the research described in chapter IV. Thanks to you it became a clearer and more thorough article. Dr K. Bosscha. Koop, thank you for your support and editoral work concerning OMA. Your creative thoughts were inspiring. Dr A. Algra. Ale, thank you for introducing me into the world of epidemiology and statistics. You took me by the hand and showed me some basics. Thank you for being there when I needed help with statistical analysis. There still remains a lot I need to learn. I am grateful for your help in chapters II and III.

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Acknowledgements

Dr D.T. Tsukayama. Dean, thank you for letting me participate in the RADAR-trial. Your positive attitude really inspired me and you were a great guest to travel with sightseeing Holland. I hope you will visit again. All experimental work described in this thesis was performed in both the clinical and experimental laboratories for medical microbiology. I would like to thank all technicians and post-docs who assisted me, especially Adrienne, Armand, Mabel, Maartje, Ali, Alice and Willem. Many thanks to all healthcare workers at the surgical ICU for enduring the different study-protocols enforced on them and maintaining high level patient care during the different study periods. The department Hospital Hygiene and Infection Prevention is acknowledged for their help in continuous monitoring and surveillance of the different hospital wards and analyses of possible epidemic outbreaks. Surgeons and fellow-residents surgery of the Amphia Hospital Breda, The Netherlands. The fantastic work climate you create is the reason why I drive those miles every day with a smile on my face. Thank you for your interest, support and the fun we have every day. Martijn Lolkema and Miquel Ekkelenkamp, my paranymphs. I am proud to have you by my side on such a special day. Martijn, we go back to the first year of medicine. We had a lot of fun and over the years you have remained a true friend, thank you. Miquel, doing research was sometimes frustrating. Drinking coffee, near the elevator on G4, while blowing off steam was good therapy. I was honored to review your first novel. It was great! Thanks you for being a colleague and a friend.

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Acknowledgements

My parents, my brother and my sister. Olav, when I was twelve you already showed me Amsterdam during my holiday visits, which made it clear to me that I had to study in Amsterdam. Your stories about Medicine, absolutely fascinated me. During my study you always looked out for me, kept me on the right track and gave me advise on how to get where I am now. I admire the courage you had to move to the UK and I am proud of what you have accomplished. Marishka, your perseverance and creativity in dance have always inspired me. Even though your whole world evolved round ballet, you never lost sight of your little brother, who has grown up now and is very proud of such a wonderful sister. Mum and dad, thank you for your unconditional love, trust and guidance. Without your continuous support and care I would not even be half the man I am today. Even though France is a little bit further than Oisterwijk, you taught us no matter what, la famiglia rimane famiglia and I know you are always there for us. Dearest Annechien, with your love and support I was able to make this thesis to what it is. You strengthen and complete me. I love you. Pepijn, my daily sunshine, at this moment you are too young to understand, but in the future I hope you will be proud.

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Curriculum vitae

Curriculum vitae The author of this thesis was born on the 15th of February 1974 in Brummen, The Netherlands. Having lived two years in the Eastern part of the country his family moved to Schoorl (NH), were he enjoyed a careless youth. During his adolescence the family lived in Oisterwijk (NB), were he attended highschool at the Maurick College in Vught. After graduating in 1992 he started medical school at the University of Amsterdam that same year. During medical school he started research in the field of palliative radiological therapy for esophagus cancer, and the familial aspects of stomach cancer at the Department of Gastro-Enterology, Antoni van Leeuwenhoek Hospital Amsterdam, The Netherlands (Dr B.G. Taal). He graduated from medical school in 1999. That year he started as a resident at the Department of Surgery, ISALA clinics, location Weezenlanden in Zwolle (Dr M. Lopez-Cardozo), where he won the “work horse” prize for his research on patient positioning during subclavian vein puncture (Dr E.G.J.M. Pierik). In 2001 the research described in this thesis was initiated at the Departments of Surgery (Prof. Dr Chr. van der Werken) and Medical Microbiology (Prof. Dr J. Verhoef), University Medical Center Utrecht, The Netherlands. In July 2003 he enrolled into the residency program for general surgery, region Utrecht (Prof. Dr I.H.M. Borel Rinkes). Currently he and his own family live in Hilversum and he is following the first part of his residency program at the Amphia Hospital, location Langendijk in Breda, The Netherlands (Dr F.J.M. van Geloven). The entire program will be completed in 2009.

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The use of Antibiotics and Implications for Antimicrobial ... · The second pathway is that of acquired resistance. Microorganisms can acquire antibiotic resistance by means of chance