title: ICU acuity: real-time models versus daily models.
abstract: OBJECTIVE
  To explore the feasibility of real-time mortality risk assessment for ICU patients.
  
  
  METHODS
  This study used retrospective analysis of mixed medical/surgical intensive care patients in a university hospital. Logistic regression was applied to 7048 development patients with several hundred candidate variables. Final models were selected by backward elimination on top cross-validated variables and validated on 3018 separate patients.
  
  
  RESULTS
  The real-time model demonstrated strong discrimination ability (Day 3 AUC=0.878). All models had circumstances where calibration was poor (Hosmer-Lemeshow goodness of fit test p < 0.1). The final models included variables known to be associated with mortality, but also more computationally intensive variables absent in other severity scores.
  
  
  CONCLUSIONS
  Real-time mortality prediction offers similar discrimination ability to daily models. Moreover, the discrimination of our real-time model performed favorably to a customized SAPS II (Day 3 AUC=0.878 vs AUC=0.849, p < 0.05) but generally had worse calibration.
authors.affiliation: CSAIL, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Caleb W
authors.initials: CW
authors.lastname: Hug
authors.forename: Peter
authors.initials: P
authors.lastname: Szolovits
mesh_terms: D019540:Area Under Curve; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units; D007902:Length of Stay; D016015:Logistic Models; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment