Importance of organ dysfunction in determining hospital outcomes in children

IMPORTANCE OF ORGAN DYSFUNCTION IN DETERMINING

HOSPITAL OUTCOMES IN CHILDREN

JOSEPH A. JOHNSTON, MD, MSC, MICHAEL S. YI, MD, MSC, MARIA T. BRITTO, MD, MPH, AND JOSEPH M. MRUS, MD, MSC

Objectives To use measures of organ dysfunction derived from administrative data to assess clinical and economic

outcomes in hospitalized children.

Study design We used the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM)

diagnostic and procedure codes to evaluate organ dysfunction in all patients, excluding neonates, in the Healthcare Cost and

Utilization Project Kids’ Inpatient Database (KID). We adapted consensus clinical definitions to characterize organ dysfunction

in terms of degree of impairment, type of organ system involvement, and number of dysfunctional organ systems. Univariate and

multivariable models were constructed to determine the impact of organ dysfunction on in-hospital mortality and resource use.

Results Patients with organ dysfunction (n = 51,386) were younger and more often male than those without organ

dysfunction, and they had significantly higher in-hospital mortality and resource use. Organ dysfunction, assessed in terms of

degree, type, and number of dysfunctional organ systems, was consistently associated with all hospital outcomes. In

multivariable models, types of organ system failures were most predictive of in-hospital mortality, whereas degree of organ

system involvement allowed for a better assessment of resource use.

Conclusions Administrative data can be used to characterize multiple dimensions of organ dysfunction in children.

Hospitalizations involving organ dysfunction are associated with significant clinical and economic consequences. (J Pediatr

2004;144:595-601)

Impairment of organ function in the acutely ill patient, resulting from either direct organinjury or from an abnormal and excessive host response to nonspecific injury, exists alonga continuum of severity. In the case of organ dysfunction as a result of sepsis, this

continuum begins with the systemic inflammatory response syndrome and advancesthrough stages involving progressively greater organ dysfunction, culminating in multipleorgan dysfunction syndrome (MODS), the point at which organ function is so impairedthat homeostasis cannot be maintained without intervention.1-3 There is mounting evi-dence that patients move sequentially through these stages and that each successive stageimposes a greater burden of mortality.4-6 In contrast to adults, children progress morequickly through these stages, are more likely to come to medical attention with simulta-neous, rather than sequential, organ system involvement, and show a different patternof organ system involvement.7

Although progressive organ dysfunction is perhaps best described for sepsis, thesame process can ensue in the presence of non-infectious conditions, such as trauma, burns,and pancreatitis. The underlying pathophysiology remains unclear, with putative rolesfor direct cytotoxic effects of proinflammatory cytokines, activation of complement andcoagulation systems, apoptosis, and ischemic tissue injury as a result of hypoperfusion and/or abnormalities of cellular uptake and utilization of oxygen.2,8-13 Organ dysfunction canpersist and progress long after resolution of the inciting insult and carries a higher mortalityrisk than most instigating disease states.14 In one of the few studies ofMODS in a pediatric

See editorial, p 562, andrelated article, p 589.

From US Outcomes Research, LillyResearch Laboratories, Indianapolis,Indiana; University of Cincinnati Med-ical Center, Cincinnati, CincinnatiChildren’s Hospital Medical Center,Cincinnati, and Health Services Re-search and Development, Depart-ment of Veterans Affairs MedicalCenter, Cincinnati, Ohio.

DrMrus is supported by aDepartmentof Veterans Affairs, Health ServicesResearch and Development ServiceCareer Development Award (RCD-01011-2).Dr Johnston is a full-time employee ofEli Lilly and Company.Submitted for publication Aug 12, 2003;last revision received Nov 20, 2003;accepted Jan 12, 2004.

Reprint requests: Joseph A. Johnston,MD, MSc, Eli Lilly and Company, LillyCorporate Center, Indianapolis, IN46285. E-mail: [email protected]/$ - see front matter

Copyrightª 2004 Elsevier Inc. All rightsreserved.

10.1016/j.jpeds.2004.01.045

ICD-9-CM International Classification of Diseases, 9thRevision, Clinical Modification

ICU Intensive care unit

KID Kids’ Inpatient DatabaseLOS Length of stayMODS Multiple organ dysfunction syndrome

595

mailto:[email protected]

intensive care unit (ICU) population, MODS was associatedwith a 54% overall mortality rate.15

Measures of organ dysfunction can be used to predictin-hospital mortality for ICU patients, and they have beenshown to add predictive information above and beyond thatprovided by general severity of illness measures in both adultsand children.16-20 Administrative data, although often used to as-sess the extent of comorbid illness,21 have been used less com-monly to assess organ dysfunction, particularly in children.22,23

In one study, administrative data were used to assess thepresence of organ dysfunction in children, but the studyexamined only patients with organ dysfunction of infectiousetiology and did not differentiate organ dysfunction on thebasis of specific conditions coded.22

The purpose of our study was to further characterizeorgan dysfunction by mapping coded diagnoses to consensusclinical definitions and to assess the importance of differentdimensions of organ dysfunction on clinical and economicoutcomes in a national sample of hospitalized children. Wehypothesized that hospital outcomes would vary substantiallyon the basis of degree of impairment, type of organ systeminvolvement, and number of dysfunctional organ systems.

METHODS

Data Source

The Healthcare Cost and Utilization Project Kids’Inpatient Database (KID) is a nationwide sample of pediat-ric discharges from community hospitals providing data tothe 22-state, all-payer 1997 Healthcare Cost and Utiliza-tion Project State Inpatient Database.24 As defined by theAmerican Hospital Association, community hospitals com-prise ‘‘all nonfederal, short-term, general and other specialtyhospitals, excluding hospital units of institutions,’’ and includeacademic medical centers and pediatric hospitals. The 1.9million discharges in the KID provide information on 10% ofuncomplicated in-hospital births and 80% of other pediatriccases from each hospital. Available data include patientdemographics and diagnosis and procedure codes, as well asoutcomes such as survival to discharge, hospital length of stay(LOS) and total hospital charges. The Agency for HealthcareResearch and Quality makes this database publicly available toenable analyses of hospital utilization by children across theUnited States.

Patient Information

We selected all hospitalizations, excluding in-hospitalbirths, for which any ICD-9-CM code for organ dysfunctionwas recorded (Appendix). We considered only codes that werelikely to represent acute processes and not chronic conditions.We classified patients in several ways on the basis of thesecodes. We first grouped codes according to the degree of organdysfunction, beginning with the definitions originally de-veloped jointly by the American College of Chest Physiciansand the Society for Critical Care Medicine to describe threelevels of progressively more severe organ dysfunction associ-ated with sepsis: ‘‘severe’’ disease, ‘‘shock,’’ and ‘‘multiple organ

596 Johnston et al

dysfunction syndrome (MODS).’’1 Because of inconsistency inthe definition of MODS, we further separated patients withcodes qualifying them for a diagnosis of MODS into thosewith only one such code (MODS1) and those with two ormore such codes (MODS2+).

1,2 These four categories werenon-overlapping; when multiple organ dysfunction codes werepresent, we assigned patients to the most severe category forwhich they met criteria. We next grouped codes into sixdistinct organ system types: respiratory, cardiac, hematologic,neurologic, renal, and hepatic; patients could qualify for one ormore of these categories. Finally, we determined the totalnumber of dysfunctional organ systems.

Statistical Analysis

We described and compared patient characteristics andoutcomes of patients with and without organ dysfunction andof subgroups of patients with different measures of organdysfunction. We report mean values with the standarddeviation and median values with the 25th and 75thpercentiles. We assessed group differences in categorical andcontinuous variables using the v2 and the Wilcoxon’s ranksum tests, respectively. We assessed the impact of increasingseverity of organ dysfunction and increasing number ofdysfunctional organ systems on hospital survival using theMantel-Haenszel v2 test of trend and on hospital LOS andtotal charges among hospital survivors and nonsurvivors usingSpearman’s correlation coefficient. We assessed the effect ofdifferent dysfunctional organ systems on mortality using thev2 test and on hospital LOS and total charges among hospitalsurvivors and nonsurvivors using analysis of variance.

We used multivariable logistic regression to assess theindependent effect of various measures of organ dysfunctionon hospital mortality. Because of nonnormal distributions ofLOS and charge data, we determined the independent effectof organ dysfunction on log-transformed LOS and log-transformed total charges using multivariable linear regres-sion. We created separate models for each measure of organdysfunction (degree, type, and number) controlling for patientage. We report odds ratios for logistic regression with 95%confidence intervals and present transformed b coefficientswith corresponding P values for linear regression models. Weevaluated model performance using the c-statistic (a measureof discrimination equivalent to the area under the receiveroperating characteristic curve where 0.5 implies discrimina-tion no better than chance and 1.0 represents perfectdiscrimination) for logistic regression and the R2 value forlinear regression models. All statistical analyses wereconducted using Statistical Analysis Systems, version 8.2(SAS Institute, Inc, Cary, NC).

RESULTSWe identified 51,386 (4.46%) pediatric hospitalizations,

excluding in-hospital births, for which at least one dischargecode for organ dysfunction was present and 1.1 millionhospitalizations without coded organ dysfunction. Patientswith organ dysfunction were significantly more likely to be

The Journal of Pediatrics � May 2004

younger and male than those without organ dysfunction(Table I). There were no meaningful differences on the basisof patient race or primary payer type. Overall, in-hospitalmortality was significantly higher (6.8% versus 0.1%), hospitalLOS significantly longer (median of 4 versus 2 days), and totalhospital charges significantly greater (median of $12,385versus $4,377) for patients with organ dysfunction comparedwith those without.

Within the cohort of patients with at least one code fororgan dysfunction, the degree, type, and number of organdysfunctions were each associated with in-hospital mortality,LOS, and total charges (Table II). Mortality was significantlyhigher among patients with shock or MODS compared withthose with only codes denoting severe organ dysfunction;patients with two or more MODS-qualifying organ dysfunc-tions had a particularly high risk of death (18.7%). Bothsurvivors and nonsurvivors with MODS had substantiallylonger LOS and higher total hospital charges than thosewith lesser degrees of organ dysfunction, although the increasewas more pronounced in hospital survivors.

Hospital outcomes also varied by organ system affected.In-hospital mortality was highest for patients with hepatic(22.6%) and renal (19.6%) dysfunction, and it was lowest forthose with cardiac (7.2%) and hematologic (8.5%) dysfunc-tion. Median LOS in survivors was longest for patients withrenal (9 days) dysfunction and shortest for those with cardiac(3 days) dysfunction. In nonsurvivors, median LOS waslongest for patients with hepatic (12 days) and renal (10 days)dysfunction and shortest for those with respiratory (3 days),cardiac (3 days), and neurologic (3 days) dysfunction. Medianhospital charges were highest for survivors with renal($25,176) and respiratory ($20,245) dysfunction and werelowest in those with cardiac ($5790) dysfunction. In non-survivors, charges were highest for those with hepatic($109,495) and renal ($90,364) dysfunction and lowest forthose with neurologic ($22,089) dysfunction.

The impact of the number of dysfunctional organsystems on outcomes was even more apparent. Mortality forpatients with one, two, three, and four or more dysfunctionalorgan systems was 4.1%, 21.6%, 43.8%, and 57.2%, respec-tively (P < .001 for trend). Hospital LOS and total chargeswere also strongly correlated with the number of dysfunctionalorgan systems, particularly for hospital survivors.

In multivariable models, age had a complex relationshipwith patient outcomes (Table III). Compared with infants,children aged 11 years and older were significantly more likelyto die, whereas all age groups, particularly children aged 1 to 6years, experienced a shorter LOS. Hospital charges weresignificantly higher for older children (aged 7-18 years) andlower for those aged 1 to 6 years. Independent of organdysfunction, in-hospital death predicted substantially shorterLOS and higher total charges.

In all models, organ dysfunction was independentlyassociated with hospital outcomes. Compared with thereference category of patients with ‘‘severe’’ disease, thepresence of shock and MODS predicted significantly highermortality, LOS, and total charges. The presence of two or

Importance of Organ Dysfunction in DeterminingHospital Outcomes in Children

more MODS-qualifying conditions (MODS2+) was associ-ated with a 22-fold increased risk of death, a 15-fold increasein hospital LOS, and an 82-fold increase in total charges.Dysfunction of each individual organ system also wasindependently associated with hospital outcomes. The stron-gest predictors of death were respiratory (OR [95% CI] 12.41[11.18-13.78]), and neurologic (OR [95% CI] 5.11 [4.57-5.72]) dysfunction, whereas respiratory and renal dysfunctionpredicted the greatest increases in resource use. Respiratorydysfunction was associated with a greater than 5-fold increasein LOS and a 25-fold increase in total charges, whereas renaldysfunction was associated with a greater than 7-fold increasein LOS and a 12-fold increase in total charges. Finally, anincrease in the number of dysfunctional organ systems wasindependently associated with incrementally higher mortality,

Table I. Patient characteristics (n = 1,152,854)

Characteristic

Organdysfunction

N (%)

No organdysfunction

N (%)P

value

Age (y) < .001<1 13,008 (25.3) 203,926 (18.5)1-2 10,233 (19.9) 158,621 (14.4)3-6 8033 (15.6) 154,556 (14.0)7-10 4952 (9.6) 114,067 (10.4)11-15 7325 (14.3) 188,452 (17.1)16-18 7835 (15.3) 281,846 (25.6)

Sex < .001Male 28,534 (55.5) 521,372 (47.3)Female 22,852 (44.5) 580,031 (52.7)

Race .16White 20,919 (40.7) 455,477 (41.4)Nonwhite 18,718 (36.4) 401,731 (36.5)Missing 11,749 (22.9) 244,260 (22.2)

Primary payer < .001Medicaid 21,174 (41.2) 438,826 (39.8)Commercial 25,064 (48.8) 549,797 (49.9)Self-pay 2226 (4.3) 59,590 (5.4)Other 2747 (5.3) 48,471 (4.4)Missing 175 (0.3) 4784 (0.4)

OutcomeOrgan

dysfunctionNo organdysfunction

Died 3489 (6.8) 1145 (0.1) < .001LOS < .001Mean (SD),days

9.6 (23.3) 3.5 (6.1)

Median [25th, 75th

percentile],days

4 [2, 10] 2 [1, 4]

Hospital charges < .001Mean (SD), $ 38,910 (91,264) 7515 (14,656)Median [25th, 75th

percentile], $12,385[4,605, 37,451]

4,377[2,628, 7,736]

597

Table II. Univariate association of different measures of organ dysfunction with hospital outcomes

Hospitalizations Mortality*

LOSy

Median [25th, 75th percentile]Total chargesy

Median [25th, 75th percentile]

Measure n (%) % Survivors Nonsurvivors Survivors Nonsurvivors

DegreeSevere 12,976 (25.3) 1.0 2 (3,5) 2 (1,8) 4584 (2513, 10,566) 17,945 (8242, 43,557)Shock 728 (1.4) 5.6 4 (2,9) 2 (1,7) 12,809 (5216, 34,504) 20,910 (9646, 51,661)MODS1 28,496 (55.5) 6.9 6 (3,11) 1 (0,4) 15,602 (6660, 36,900) 9576 (3225, 32,442)MODS2+ 9186 (17.9) 18.7 11 (5,21) 5 (1,17) 43,558 (18,496, 94,342) 36,855 (15,845, 114,610)

TypeRespiratory 28,640 (55.7) 10.4 6 (3,13) 3 (1,11) 20,245 (7068, 53,056) 27,711 (12,333, 75,000)Cardiac 15,334 (29.8) 7.2 3 (2,7) 3 (1,12) 5790 (2786, 21,208) 26,250 (12,225, 85,547)Hematologic 8004 (15.6) 8.5 5 (3,11) 5 (1,18) 12,658 (5376, 37,165) 40,865 (17,500, 134,129)Neurologic 4430 (8.6) 13.1 5 (2,12) 3 (1,5) 12,121 (5445, 32,407) 22,089 (11,532, 38,692)Renal 2192 (4.3) 19.6 9 (4,18) 10 (3,26) 25,176 (8575, 68,426) 90,364 (25,378, 243,005)Hepatic 456 (0.9) 22.6 6 (3,18) 12 (4,27) 15,657 (6321, 58,156) 109,495 (36,870, 211,936)

Number1 45,274 (88.1) 4.1 4 (2,9) 2 (1,10) 10,006 (4062, 29,715) 23,903 (10,308, 61,540)2 4854 (9.5) 21.6 11 (5,21) 3 (1,13) 41,797 (17,512, 94,035) 30,099 (13,134, 85,753)3 1007 (2.0) 43.8 17 (9,32) 3 (1,15) 80,273 (39,354, 116,592) 33,326 (14,714, 109,249)$4 251 (0.5) 57.2 22 (11,35) 5 (2,16) 95,990 (48,512, 170,209) 62,360 (21,305, 168,232)

*Trends toward increasing mortality with increasing degree and number of organ failures were statistically significant (P< .0001 using theMantel-Haenszel v2 test of trend). Differences in mortality based upon type of organ failure were also statistically significant (P< .0001 using v2 test).yCorrelations between degree and number of organ failures and both LOS and total charges were statistically significant for survivors and nonsurvivors(P< .0001 for all Spearman’s correlation coefficients). Variance in LOS and total charges as a function of type of organ failure was also statisticallysignificant (P< .0001 using one-way analysis of variance) for survivors and nonsurvivors.

LOS, and total charges. The addition of a second organ systeminvolvement predicted a greater than 6-fold increased odds ofdeath, a 5-fold increase in LOS, and a 12-fold increase in totalcharges. The increase in the odds of death and in total chargeswith each additional organ dysfunction was more than addi-tive, whereas the increase in LOS was less than additive.

In terms of overall model performance, all three modelsdiscriminated between survivors and nonsurvivors moderatelywell. The model incorporating dysfunctional organ systemtypes discriminated somewhat better (c-statistic = 0.786)than did models with degree (c-statistic = 0.745) or number(c-statistic = 0.736) of organ dysfunctions. In contrast, themodel incorporating degree of organ dysfunction accountedfor a greater portion of the variability in LOS (R2 = 0.13) andcharges (R2 = 0.23) than did the models with type (R2 = 0.10for LOS; R2 = 0.21 for charges) or number (R2 = 0.06 forLOS; R2 = 0.12 for charges) of organ dysfunctions.

DISCUSSIONAlthough organ dysfunction has consistently been

shown to be associated with hospital outcomes in manydisease states, including MODS, few studies have examinedthe significance of different measures of organ dysfunctionmore generally across disease states. Our results demonstratethat the presence of organ dysfunction in hospitalizedchildren, assessed using administrative data, is strongly

598 Johnston et al

associated with adverse clinical and economic outcomes.Differentiating patients on the basis of degree, type, andnumber of organ dysfunctions permits identification of sub-groups with distinctly different outcomes. Respiratory, neu-rologic, and renal dysfunction, in particular, appear to beespecially predictive of higher mortality and greater resourceuse. The optimal representation of organ dysfunction appearsto depend on the outcome being examined, with knowledgeof the involvement of specific organ systems being most help-ful in predicting mortality and information about degreeof organ system involvement being more indicative of re-source use.

It is interesting to compare our findings with those ofprevious investigations into organ dysfunction among chil-dren. Whereas the overall mortality rate we observed for allpatients with organ dysfunction is similar (6.8%) to theunderlying ICUmortality rates seen in several previous studies(6%-11%),4,5,15 these and other studies have shown mortalityrates between 36% and 54% for patients meeting clinicalcriteria for MODS (or ‘‘multiple organ system fail-ure’’),4,5,15,25,26 higher than what we observed in our patientswith two or more dysfunctional organ systems (26.7%) ormeeting our MODS2+ criteria (18.7%). There are a number ofpossible explanations for this. First, our cohort may includepatients never admitted to an ICU, and it excludes neonates,known to be a higher risk subgroup.22,25 Second, our approachto defining organ dysfunction, with its reliance on coded


Table III. Multivariable predictors of hospital outcomes

PredictorMortality* adjustedodd ratio [95% CI]

LOS transformed bcoefficient (P value)

Total charges transformedb coefficient (P value)

Model 1y

Age (y)1-2 0.91 (0.81-1.03) 0.53 (< .0001) 0.51 (< .0001)3-6 0.95 (0.84-1.08) 0.61 (< .0001) 0.73 (< .0001)7-10 1.08 (0.94-1.24) 0.84 (< .0001) 1.15 (.0039)11-15 1.36 (1.21-1.52) 0.93 (.0444) 1.55 (< .0001)16-18 1.64 (1.48-1.83) 0.80 (< .0001) 1.33 (< .0001)

Degree of organ dysfunctionShock 7.16 (5.11-10.02) 3.76 (< .0001) 9.08 (< .0001)MODS1 5.80 (4.84-6.96) 2.89 (< .0001) 7.60 (< .0001)MODS2+ 22.47 (18.72-26.97) 15.04 (< .0001) 82.73 (< .0001)

In-hospital death — 0.29 (< .0001) 1.94 (< .0001)Model 2z

Age (y)1-2 0.92 (0.82-1.04) 0.51 (< .0001) 0.51 (< .0001)3-6 0.99 (0.87-1.12) 0.58 (< .0001) 0.74 (< .0001)7-10 1.16 (1.01-1.34) 0.79 (< .0001) 1.18 (.0008)11-15 1.51 (1.34-1.70) 0.91 (.0112) 1.69 (< .0001)16-18 1.94 (1.74-2.17) 0.81 (< .0001) 1.52 (< .0001)

Type of organ dysfunctionRespiratory 12.41 (11.18-13.78) 5.86 (< .0001) 25.18 (< .0001)Cardiac 2.93 (2.69-3.20) 1.62 (< .0001) 2.14 (< .0001)Hematologic 3.10 (2.78-3.46) 3.96 (< .0001) 7.73 (< .0001)Neurologic 5.11 (4.57-5.72) 3.13 (< .0001) 4.80 (< .0001)Renal 4.61 (3.98-5.33) 7.23 (< .0001) 12.88 (< .0001)Hepatic 3.67 (2.66-5.08) 3.83 (< .0001) 5.72 (< .0001)

In-hospital death — 0.25 (< .0001) 1.50 (< .0001)Model 3§

Age (y)1-2 0.87 (0.77-0.98) 0.48 (< .0001) 0.44 (< .0001)3-6 0.92 (0.82-1.05) 0.60 (< .0001) 0.70 (< .0001)7-10 1.09 (0.95-1.26) 0.87 (.0006) 1.24 (< .0001)11-15 1.39 (1.24-1.56) 0.96 (.2965) 1.67 (< .0001)16-18 1.76 (1.58-1.97) 0.84 (< .0001) 1.49 (< .0001)

Number of organ dysfunctions2 6.39 (5.88-6.95) 5.51 (< .0001) 12.76 (< .0001)3 18.46 (16.15-21.11) 8.85 (< .0001) 28.84 (< .0001)$4 31.27 (24.19-40.43) 10.54 (< .0001) 38.17 (< .0001)

In-hospital death — 0.31 (< .0001) 2.30 (< .0001)

*Summary c-statistics: 0.745 for model 1, 0.786 for model 2, and 0.736 for model 3.yReference group = infants with only organ dysfunction classified as ‘‘severe’’ surviving to discharge.zReference group = infants without each given organ dysfunction surviving to discharge.§Reference group = infants with only a single organ dysfunction surviving to discharge.

diagnoses and procedures, is more likely to omit certain organfailures (eg, gastrointestinal) and lesser degrees of organdysfunction that are more easily captured when screeningprospectively using clinical criteria, rather than screeningretrospectively with diagnostic codes. Finally, the presence ofmultiple organ failures in our patients may or may not havebeen concurrent (a requirement for ‘‘true’’ MODS).


Other investigators also have demonstrated mortalitydifferences as a function of specific organ system fail-ures.15,25,26 Whereas our US cohort had a considerably loweroverall mortality than the Peruvian cohort of patients withMODS recently described by Tantalean and colleagues,26

their finding that patients with hepatic, renal, and neurologicdysfunction had the highest unadjusted mortality rates is

599

consistent with ours. Furthermore, our finding that respiratorydysfunction has the greatest independent effect on mortalityis consistent with the only previous study to report results ofan adjusted analysis of mortality as a function of the involve-ment of organ system types in pediatric ICU patients.15 Thedifference between univariate and multivariable results is dueto the fact that patients with hepatic and renal dysfunctionhave, on average, a greater number of organ dysfunctions (2.1and 1.8, respectively) than those with respiratory dysfunction(1.2). The regression results eliminate this confounding effectof multiple organ dysfunctions and reveal the independentassociation of each organ dysfunction with mortality. Inaddition, the mortality rates we observed for patients with anygiven number of dysfunctional organ systems are consistentwith those observed in previous studies: 4.1% versus 1% to 7%for one, 21.6% versus 11% to 29.4% for two, 43.8% versus38.8% to 62% for three, and 57.2% versus 53.1% to 88% forfour or more organ failures.5,15,22,25,26

Comparison of hospital LOS is also complicated bydifferences in populations. Studies of MODS generally re-port a median patient ICU LOS of 2 to 4 days, but they donot report hospital LOS or differentiate survivors fromnonsurvivors.4,5,15,25 Similar to our findings, Tantalean andcolleagues report longer median hospital LOS for survivorswith MODS (7 days) than for survivors without MODS (3.4days) and incremental increase in median LOS with increasingnumber of organ failures (5.9, 9.7, and 16 days for survivorswith two, three, and four organ failures, respectively),although this was for a non-US cohort of ICU patients.26

An examination of total hospital charges is alsoinformative. Consistent with other studies, we found thatcharges were generally higher for nonsurviving patients thanfor survivors.27,28 This pattern, however, was reversed forpatients with one or more MODS-qualifying conditions(MODS1 and MODS2+) and for the relatively few patientswith two or more organ dysfunctions. This is explainedprincipally by the substantially longer median hospital LOSfor survivors with this degree of organ dysfunction relative tononsurvivors. Also noteworthy is that respiratory and renaldysfunction predicted longer hospital LOS and higher chargesthan other conditions, whereas in other studies patients withcirculatory failure tended to generate the highest ICUcosts.27,28 Further comparison is problematic as these studiesreport only ICU-specific costs and categorize patientsdifferently.

Other researchers have described the limitations ofadministrative data, and our study shares these limitations.29

Patient-level information regarding the precise reason forhospital admission, location of care within the hospital, historyof prior hospitalizations, and acute physiologic status (eg, vitalsigns or laboratory data) were unavailable. Furthermore, thestatic nature of discharge data limits our ability to understandthe underlying disease process leading to a given diagnosis orthe complex relationship between organ dysfunction andoutcomes. Importantly, we can’t determine whether a givenorgan system failure precedes or follows any other, or whetherit leads to or results from a concomitant organ dysfunction.

600 Johnston et al

Finally, neither true cost data nor hospital-specific cost-to-charge ratios are available in the KID database, necessitatingthe use of charges as a proxy for costs. Charges are known tooverestimate true costs and to vary more widely from site tosite than costs.30

In summary, our findings support the concept that organdysfunction is a significant occurrence in hospitalized children,leading to significant adverse clinical and economic con-sequences. Important dimensions of organ dysfunction toconsider include degree, type, and number of organ systeminvolvement, with type and degree of impairment being mostimportant in predicting mortality and resource use, respec-tively. An awareness of these findings may assist in the designof further research studies investigating organ dysfunction inchildren and in the development of future hospital-basedquality improvement efforts.

We acknowledge the helpful suggestions of two anonymousreviewers.

REFERENCES1. American College of Chest Physicians/Society of Critical Care

Medicine Consensus Conference. Definitions for sepsis and organ failure

and guidelines for the use of innovative therapies in sepsis. Crit Care Med

1992;20:864-74.

2. Saez-Llorens X, McCracken GH Jr. Sepsis syndrome and septic shock

in pediatrics: current concepts of terminology, pathophysiology, and

management. J Pediatr 1993;123:497-508.

3. Bone RC, Grodzin CJ, Balk RA. Sepsis: a new hypothesis for

pathogenesis of the disease process. Chest 1997;112:235-43.

4. Proulx F, Fayon M, Farrell CA, Lacroix J, Gauthier M. Epidemiology

of sepsis and multiple organ dysfunction syndrome in children. Chest 1996;

109:1033-7.

5. Wilkinson JD, PollackMM,Glass NL, Kanter RK, Katz RW, Steinhart

CM. Mortality associated with multiple organ system failure and sepsis in

pediatric intensive care unit. J Pediatr 1987;111:324-8.

6. Rangel-Frausto MS, Pittet D, Costigan M, Hwang T, Davis CS,

Wenzel RP. The natural history of the systemic inflammatory response

syndrome (SIRS): a prospective study. JAMA 1995;273:117-23.

7. Steinhorn D, Cerra F. Multiple organ dysfunction syndrom. In:

Fuhrman B, Zimmerman J, eds. Pediatric Critical Care. St. Louis: Mosby

Year Book; 1998: 955-65.

8. Fink MP. Bench-to-bedside review: cytopathic hypoxia. Crit Care

2002;6:491-9.

9. Sair M, Etherington PJ, Winlove CP, Evans TW. Tissue oxygenation

and perfusion in patients with systemic sepsis. Crit Care Med 2001;29:

1343-9.

10. Carcillo J, Pollack MM, Ruttimann UE, Fields AI. Sequential

physiologic interactions in pediatric cardiogenic and septic shock. Crit Care

Med 1989;17:12-6.

11. Hotchkiss RS, Karl IE. The pathophysiology and treatment of sepsis.

N Engl J Med 2003;348:138-50.

12. Hotchkiss RS, et al. Rapid onset of intestinal epithelial and lymphocyte

apoptotic cell death in patients with trauma and shock. Crit Care Med

2000;28:3207-17.

13. Rivers E, et al. Early goal-directed therapy in the treatment of severe

sepsis and septic shock. N Engl J Med 2001;345:1368-77.

14. Saez-Llorens X, Lagrutta F. The acute phase host reaction during

bacterial infection and its clinical impact in children. Pediatr Infect Dis J

1993;12:83-7.

15. Wilkinson JD, Pollack MM, Ruttimann UE, Glass NL, Yeh TS.

Outcome of pediatric patients with multiple organ system failure. Crit Care

Med 1986;14:271-4.


16. Barie PS, Hydo LJ, Fischer E. A prospective comparison of two multiple

organ dysfunction/failure scoring systems for prediction of mortality in critical

surgical illness. J Trauma 1994;37:660-6.

17. Timsit JF, et al. Accuracy of a composite score using daily SAPS II and

LOD scores for predicting hospital mortality in ICU patients hospitalized for

more than 72 h. Intensive Care Med 2001;27:1012-21.

18. Janota J, Stranak Z, Statecna B, Dohnalova A, Sipek A, Simak J.

Characterization of multiple organ dysfunction syndrome in very low

birthweight infants: a new sequential scoring system. Shock 2001;15:348-52.

19. Pettila V, Pettila M, Sarna S, Voutilainen P, Takkunen O. Comparison

of multiple organ dysfunction scores in the prediction of hospital mortality in

the critically ill. Crit Care Med 2002;30:1705-11.

20. Talmor M, Hydo L, Barie PS. Relationship of systemic inflammatory

response syndrome to organ dysfunction, length of stay, and mortality in critical

surgical illness: effectof intensive careunit resuscitation.ArchSurg1999;134:81-7.

21. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity

index for use with ICD-9-CM administrative databases. J Clin Epidemiol

1992;45:613-9.

22. Watson RS, Carcillo JA, Linde-Zwirble WT, Clermont G, Lidicker J,

Angus DC. The epidemiology of severe sepsis in children in the United

States. Am J Respir Crit Care Med 2003;167:695-701.

23. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J,

Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of


incidence, outcome, and associated costs of care. Crit Care Med 2001;

29:1303-10.

24. Agency for Healthcare Research and Quality: HCUP Kids’ Inpatient

Database (KID). Available online at: http://www.ahcpr.gov/data/hcup/

hcupkid.htm [access 2003 June].

25. Proulx F, Gauthier M, Nadeau D, Lacroix J, Farrell CA. Timing and

predictors of death in pediatric patients with multiple organ system failure.

Crit Care Med 1994;22:1025-31.

26. Tantalean JA, Leon RJ, Santos AA, Sanchez E. Multiple org-

an dysfunction syndrome in children. Pediatr Crit Care Med 2003;4:

181-5.

27. Chalom R, Raphaely RC, Costarino AT Jr. Hospital costs of pediatric

intensive care. Crit Care Med 1999;27:2079-85.

28. Seferian EG, Carson SS, Pohlman A, Hall J. Comparison of resource

utilization and outcome between pediatric and adult intensive care unit

patients. Pediatr Crit Care Med 2001;2:2-8.

29. Iezzoni LI. Assessing quality using administrative data. Ann InternMed

1997;127:666-74.

30. Finkler SA. The distinction between cost and charges. Ann Intern Med

1982;96:102-9.

31. Carcillo JA, Fields AI. Task Force Committee Members. Clinical

practice parameters for hemodynamic support of pediatric and neonatal

patients in septic shock. Crit Care Med 2002;30:1365-78.

APPENDIX

Definitions of organ dysfunction

Condition Criteria ICD-9-CM codes*

Severe Evidence of altered organ perfusion with at least one of thefollowing: acute changes in consciousness, oliguria,elevated blood lactate, hypoxemia, and hypotension orpoor capillary refill that responds rapidly (ie, <1 hour)to parenteral fluids

Acute delirium (293.1); subacute delirium (293.2);encephalopathy (348.3); oliguria and anuria(788.5); acidosis (276.2); hypotension (458)

Shock Hypotensiony or poor capillary refill in a patient with severesepsis that does not reverse rapidly after parenteral fluidsand requires the use of vasoactive drugs.

Shock (785.5)

MODS Any combination of disseminated intravascular coagulation,acute respiratory distress syndrome, acute renal failure,hepatobiliary dysfunction, or neurologic dysfunctionin a patient meeting criteria for ‘‘severe’’ diseaseor ‘‘shock.’’

Defibrination syndrome (includes DIC) (286.6);other/unspecified coagulation defect (286.9);secondary thrombocytopenia (287.4)z;thrombocytopenia, unspecified (287.5)z; acuterespiratory distress syndrome (518.5); acuterespiratory failure NOS (518.81); acute respiratorydistress/insufficiency, not elsewhere classified (518.82);mechanical ventilation (96.7); acute renal failure(584); acute and subacute necrosis of liver (570); hepaticinfarction (573.4); anoxic brain damage (348.1)

DIC, Disseminated intravascular coagulation; NOS, not otherwise specified.*A table containing the percentage of patients in each category with each ICD-9-CM code is available from the authors on request.yBecause children, compared with adults, compensate well for shock states with tachycardia and vasoconstriction, hypotension is much less likely to present. Theclinical diagnosis of shock thus depends on the presence of thermal dysregulation (hypothermia or hyperthermia) and clinical signs of decreased perfusion, suchas decreased mental status, prolonged capillary refill, diminished pulses, or decreased urine output.31

zThrombocytopenia occurring in the setting of acute critical illness should be coded ‘‘secondary’’ or ‘‘unspecified’’ thrombocytopenia. ‘‘Primary’’thrombocytopenia (ICD-9-CM code 287.3), which includes idiopathic thrombocytopenic purpura (ITP), is less likely to occur in this setting and was excluded.

601

Documents

Importance of organ dysfunction in determining hospital outcomes in children