Predicting nosocomial bloodstream infections using surrogate markers of injury severity: clinical and methodological perspectives.
BACKGROUND
Injury severity indices are numerical scores that are utilized to predict nosocomial bloodstream infections (BSI) in critically ill patients. However, surrogate markers of injury severity (SMIS) may be more clinically meaningful than these commonly used numerical injury severity indices with respect to the control and prevention of nosocomial BSI.


OBJECTIVE
The purpose of this study was to demonstrate the clinical and research implications of using the SMIS in predicting nosocomial BSI.


METHODS
A prospective nonexperimental cohort study was conducted on 361 critically ill trauma patients. Three logistic regression models were examined for their clinical relevance and statistical parsimony. The first model included the Injury Severity Score (ISS) and 5 other independent predictors, and excluded the SMIS. The second model included all study variables. The third model excluded the ISS.


RESULTS
The analysis suggested that number of blood units transfused, number of central venous catheters inserted, and use of chest tube(s) were the SMIS. The ISS was found to be an independent predictor of nosocomial BSI only when the SMIS were not included in the model. The model that included the SMIS and excluded the ISS explained the highest variance in nosocomial BSI and had the best negative predictive value (93%).


CONCLUSIONS
Clinicians can use knowledge of SMIS to develop interventions that minimize the risk of nosocomial BSI. Hence, the SMIS can serve not only as a prediction tool but also as a way to enhance control and prevention strategies for BSI.
El-Masri
Maher M
MM
University of Windsor, Faculty of Nursing, Windsor, Ontario, Canada. melmasri@uwindsor.ca
Hammad
Tarek A
TA
Fox-Wasylyshyn
Susan M
SM
D000704:Analysis of Variance; D002405:Catheterization, Central Venous / Q000009:adverse effects; D015505:Chest Tubes / Q000009:adverse effects; D016638:Critical Illness; D003428:Cross Infection / Q000175:diagnosis / Q000453:epidemiology / Q000209:etiology*; D006801:Humans; D007166:Immunosuppressive Agents / Q000009:adverse effects; D017053:Infection Control / Q000379:methods; D015601:Injury Severity Score; D007902:Length of Stay / Q000706:statistics & numerical data; D016014:Linear Models; D016015:Logistic Models; D008873:Mid-Atlantic Region / Q000453:epidemiology; D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods* / Q000592:standards; D012680:Sensitivity and Specificity; D018805:Sepsis / Q000175:diagnosis / Q000453:epidemiology / Q000209:etiology*; D012709:Serum Albumin / Q000378:metabolism; D065227:Transfusion Reaction; D014193:Trauma Centers; D014947:Wounds and Injuries / Q000145:classification / Q000150:complications
D007166:Immunosuppressive Agents; D012709:Serum Albumin