title: The identification of ICU-specific outcome predictors: a comparison of medical, surgical, and cardiothoracic ICUs from a single institution.
abstract: OBJECTIVE
  To identify ICU-specific predictors of mortality.
  
  
  METHODS
  An inception cohort study.
  
  
  METHODS
  Barnes Hospital, an academic tertiary care center.
  
  
  METHODS
  Consecutive patients, requiring mechanical ventilation, admitted to the medical intensive care unit (ICU) (75 patients), surgical ICU (100 patients), and cardiothoracic ICU (102 patients).
  
  
  METHODS
  Prospective data collection and outcomes evaluation.
  
  
  RESULTS
  Stepwise logistic regression analysis identified the following variables to be independent predictors of mortality for the individual ICUs: medical ICU, an Organ System Failure Index (OSFi) greater than or equal to 3; surgical ICU, OSFI greater than or equal to 3; cardiothoracic ICU, OSFI greater than or equal to 3, requiring acute dialysis, and the occurrence of an iatrogenic event. The same analysis was repeated after removing the OSFI as a potential confounding variable. Independent predictors of mortality identified in this subsequent analysis were as follows: medical ICU, occurrence of renal failure; surgical ICU, supine head positioning, acute physiology score greater than or equal to 10, preadmission lifestyle score greater than or equal to 2; cardiothoracic ICU, requiring acute dialysis, occurrence of ventilator-associated pneumonia, and the occurrence of an iatrogenic event.
  
  
  CONCLUSIONS
  We identified the presence of ICU-specific predictors of mortality amongst the three ICUs examined. These data suggest that ICU-specific interventions could be developed to improve the quality of patient care and potentially to reduce patient mortality.
authors.affiliation: Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: M H
authors.initials: MH
authors.lastname: Kollef
mesh_terms: D018806:APACHE; D000046:Academic Medical Centers; D000368:Aged; D002318:Cardiovascular Diseases / Q000401:mortality; D015331:Cohort Studies; D003325:Coronary Care Units / Q000592:standards / Q000706:statistics & numerical data; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000592:standards / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008923:Missouri / Q000453:epidemiology; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care; D011379:Prognosis; D012121:Respiration, Artificial; D013514:Surgical Procedures, Operative / Q000401:mortality; D016019:Survival Analysis