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Medical University of Vienna Jeroen S. de Bruin Healthcare-Associated Infections Definition according to the ECDC: An infection is considered as [healthcare]-associated if it occurs later than 48 hours after admittance to a [healthcare] facility. Commonly abbreviated as either HAI, or HCAI.
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Medical University of Vienna Jeroen S. de Bruin
Validation of Fuzzy Logic in Infection Surveillance
Jeroen S. de Bruin, Alexander Blacky, Walter Koller, Klaus-Peter Adlassnig
Medical University of Vienna Jeroen S. de Bruin
About me…
University Assistant at the Medical University of Vienna
Main research topicThe electronic detection of healthcare-associated infections
Medical University of Vienna Jeroen S. de Bruin
Healthcare-Associated Infections
Definition according to the ECDC:
An infection is considered as [healthcare]-associated if it occurs later than 48 hours after admittance to a [healthcare] facility.
Commonly abbreviated as either HAI, or HCAI.
Medical University of Vienna Jeroen S. de Bruin
HAI types
Various (main) types of HAI, depending on infection site:
• Blood stream infection (BSI)• Pneumonia (PN)• Urinary tract infection (UTI)• Central venous catheter-related infection (CRI)• Surgical site infection (SSI)
Medical University of Vienna Jeroen S. de Bruin
Electronic detection data
PDMS Biochemistry
Microbiology
Medical University of Vienna Jeroen S. de Bruin
Electronic detection system
Medical University of Vienna Jeroen S. de Bruin
Fuzzy set theory• Perform a qualitative abstraction on quantifiable
data.• Calculating the compatibility between the
patient’s measurable health status and an abstract linguistic clinical concept
Fuzzy logic• Inference mechanisms to reason about more
abstract clinical concepts using fuzzy sets.
Fuzzy set theory & Logic
Medical University of Vienna Jeroen S. de Bruin
Why use Fuzzy?
Fuzzy set theory and logic introduce graduality
• Infections and infection signs no longer simply appear, but the development process can be seen and tracked
Potential clinical uses:• Patterns & prediction• Early intervention• Correct classification of HAIs
Medical University of Vienna Jeroen S. de Bruin
Practical example
Make fixed (crisp) thresholds fuzzy!• Fuzzy region of fever between 37.5 and 38
degrees
Medical University of Vienna Jeroen S. de Bruin
Fever fuzzy set
Medical University of Vienna Jeroen S. de Bruin
Blood stream infection
Medical University of Vienna Jeroen S. de Bruin
Choice of fuzzy threshold• How to determine if the threshold was adequately
chosen?• Can it be wider? Is it too wide?
Hypothesis• Patients with a fuzzy indication of HAI tend to
have fuzzy values for infection indicators (e.g. fever, hypotension, leukopenia, etc) more often
Fuzzy threshold valid?
Medical University of Vienna Jeroen S. de Bruin
Validation experiment
• Period: January – December 2011• #Stations: 10 intensive care units• #Patients: 2,429• #Patient days: 24,487• Infection subset: CRI
Medical University of Vienna Jeroen S. de Bruin
Validation resultsInfection Parameter No infection signs Fuzzy CRI signs p
#Fuzzy values (%) #Fuzzy values (%)
Increased body temperature 14.1 20
0.003
Shock 27.2 38< 0.001
Increased C-reactive protein 24.0 77
< 0.001
Leukopenia 2.7 7< 0.001
Leukocytosis 6.3 90.032
Fever 61.8 90 < 0.001
Hypotension 65.4 68 0.297
Clinical signs of BSI 20.6 100< 0.001
Medical University of Vienna Jeroen S. de Bruin
Validation resultsInfection Parameter No infection signs Fuzzy CRI signs p
#Fuzzy values (%) #Fuzzy values (%)
Increased body temperature 14.1 20
0.003
Shock 27.2 38< 0.001
Increased C-reactive protein 24.0 77
< 0.001
Leukopenia 2.7 7< 0.001
Leukocytosis 6.3 90.032
Fever 61.8 90 < 0.001
Hypotension 65.4 68 0.297
Clinical signs of BSI 20.6 100< 0.001
Medical University of Vienna Jeroen S. de Bruin
Conclusions
• Fuzzy logic can be used effectively to detect patients with mild or partial signs of infection
• Potential clinical uses for this method include:– Prediction– Early intervention– Accurate classification of HAI
Medical University of Vienna Jeroen S. de Bruin
Thank you!
• Many thanks go out to:– Dr. Harald Mandl– The Clinical Institute of Hospital Hygiene