title: A model to predict short-term death or readmission after intensive care unit discharge.
abstract: OBJECTIVE
  Early unplanned readmission to the intensive care unit (ICU) carries a poor prognosis, and post-ICU mortality may be related, in part, to premature ICU discharge. Our objectives were to identify independent risk factors for early post-ICU readmission or death and to construct a prediction model.
  
  
  METHODS
  Retrospective analysis of a prospective database was done.
  
  
  METHODS
  Four ICUs of the French Outcomerea network participated.
  
  
  METHODS
  Patients were consecutive adults with ICU stay longer than 24 hours who were discharged alive to same-hospital wards without treatment-limitation decisions.
  
  
  RESULTS
  Of 5014 admitted patients, 3462 met our inclusion criteria. Age was 60.6 ± 17.6 years, and admission Simplified Acute Physiology Score II (SAPS II) was 35.1 ± 15.1. The rate of death or ICU readmission within 7 days after ICU discharge was 3.0%. Independent risk factors for this outcome were age, SAPS II at ICU admission, use of a central venous catheter in the ICU, Sepsis-related Organ Failure Assessment and Systemic Inflammatory Response Syndrome scores before ICU discharge, and discharge at night. The predictive model based on these variables showed good calibration. Compared with SAPS II at admission or Stability and Workload Index for Transfer at discharge, discrimination was better with our model (area under receiver operating characteristics curve, 0.74; 95% confidence interval, 0.68-0.79).
  
  
  CONCLUSIONS
  Among patients without treatment-limitation decisions and discharged alive from the ICU, 3.0% died or were readmitted within 7 days. Independent risk factors were indicators of patients' severity and discharge at night. Our prediction model should be evaluated in other ICU populations.
authors.affiliation: Intensive Care Unit, Saint-Joseph Hospital, Paris, France.
authors.forename: Islem
authors.initials: I
authors.lastname: Ouanes
authors.forename: Carole
authors.initials: C
authors.lastname: Schwebel
authors.forename: Adrien
authors.initials: A
authors.lastname: Français
authors.forename: Cédric
authors.initials: C
authors.lastname: Bruel
authors.forename: François
authors.initials: F
authors.lastname: Philippart
authors.forename: Aurélien
authors.initials: A
authors.lastname: Vesin
authors.forename: Lilia
authors.initials: L
authors.lastname: Soufir
authors.forename: Christophe
authors.initials: C
authors.lastname: Adrie
authors.forename: Maïté
authors.initials: M
authors.lastname: Garrouste-Orgeas
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Timsit
authors.forename: Benoît
authors.initials: B
authors.lastname: Misset
mesh_terms: D000367:Age Factors; D000368:Aged; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000706:statistics & numerical data; D008875:Middle Aged; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011379:Prognosis; D012189:Retrospective Studies; D012307:Risk Factors