title: Can we predict prognosis using mortality probability model IIo?
abstract: OBJECTIVE
  To evaluate Mortality Probability Model (MPM) IIo as a tool to predict very poor prognosis after intensive care unit admission.
  
  
  METHODS
  The study was conducted as a prospective observational study in a medical-surgical intensive care unit in a tertiary care teaching hospital, Riyadh, Kingdom of Saudi Arabia. Data necessary to calculate MPM IIo predicted mortality was collected from March 1999 through to February 2000 on all intensive care unit admissions. The hospital outcome was documented. We calculated the sensitivity, specificity, positive predictive value and negative predictive value of MPM IIo using cutoff points of 90% and 95%.
  
  
  RESULTS
  Data was complete on 557/569 patients (98%). Thirty-one patients had predicted mortality of >95% and all died yielding a specificity of 100% and positive predictive value of 100%. However, sensitivity was only 18% and negative predictive value 73%. Forty-four patients had predicted mortality of >90% of whom only one survived yielding a specificity of 99.7% and a positive predictive value of 97.7%. Sensitivity was only 25% and negative predictive value of 75%.
  
  
  CONCLUSIONS
  Using a decision-cutoff of 95% predicted mortality using MPMI IIo had a very high specificity in predicting death after intensive care unit admission, although with a low sensitivity. This information can be used to support clinical judgment regarding the very ill patients who are unlikely to benefit from intensive care unit admission.
authors.affiliation: Intensive Care Department, MC 1425, King Fahad National Guard Hospital, PO Box 22490, Riyadh 11426, Kingdom of Saudi Arabia. arabi@ngha.med.sa
authors.forename: Yaseen
authors.initials: Y
authors.lastname: Arabi
authors.forename: Radoslow
authors.initials: R
authors.lastname: Goraj
authors.forename: Abdullah
authors.initials: A
authors.lastname: Al-Shimemeri
authors.forename: Salim
authors.initials: S
authors.lastname: Al-Malik
mesh_terms: D000328:Adult; D000368:Aged; D016638:Critical Illness / Q000401:mortality*; D005260:Female; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012529:Saudi Arabia