title: Decisions to forgo life-sustaining therapy in ICU patients independently predict hospital death.
abstract: OBJECTIVE
  More than one-half the deaths of patients admitted to intensive care units (ICUs) occur after a decision to forgo life-sustaining therapy (DFLST). Although DFLSTs typically occur in patients with severe comorbidities and intractable acute medical disorders, other factors may influence the likelihood of DFLSTs. The objectives of this study were to describe the factors and mortality associated with DFLSTs and to evaluate the potential independent impact of DFLSTs on hospital mortality.
  
  
  METHODS
  Prospective multicenter 2-year study in six ICUs in France.
  
  
  METHODS
  The 1,698 patients admitted to the participating ICUs during the study period, including 295 (17.4%) with DFLSTs.
  
  
  RESULTS
  The impact of DFLSTs on hospital mortality was evaluated using a model that incorporates changes in daily logistic organ dysfunction scores during the first ICU week. Univariate predictors of death included demographic factors (age, gender), comorbidities, reasons for ICU admission, severity scores at ICU admission, and DFLSTs. In a stepwise Cox model five variables independently predicted mortality: good chronic health status (hazard ratio, 0.479), SAPS II score higher than 39 (2.05), chronic liver disease (1.463), daily logistic organ dysfunction score (1.357 per point), and DFLSTs (1.887).
  
  
  CONCLUSIONS
  DFLSTs remain independently associated with death after adjusting on comorbidities and severity at ICU admission and within the first ICU week. This highlights the need for further clarifying the many determinants of DFLSTs and for routinely collecting DFLSTs in studies with survival as the outcome variable of interest.
authors.affiliation: Saint-Louis Teaching Hospital, Medical ICU Department, 1 Avenue Claude Vellefaux, 75010, Paris, France. elie.azoulay@outcomerea.org
authors.forename: Elie
authors.initials: E
authors.lastname: Azoulay
authors.forename: Frédéric
authors.initials: F
authors.lastname: Pochard
authors.forename: Maité
authors.initials: M
authors.lastname: Garrouste-Orgeas
authors.forename: Delphine
authors.initials: D
authors.lastname: Moreau
authors.forename: Laurent
authors.initials: L
authors.lastname: Montesino
authors.forename: Christophe
authors.initials: C
authors.lastname: Adrie
authors.forename: Arnaud
authors.initials: A
authors.lastname: de Lassence
authors.forename: Yves
authors.initials: Y
authors.lastname: Cohen
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Timsit
mesh_terms: D018806:APACHE; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D015897:Comorbidity; D003422:Critical Care / Q000706:statistics & numerical data*; D003657:Decision Making; D005260:Female; D017052:Hospital Mortality; D006784:Hospitals, Teaching; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D008020:Life Support Care / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D010297:Paris / Q000453:epidemiology; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D016414:Resuscitation Orders; D012307:Risk Factors; D012720:Severity of Illness Index; D016019:Survival Analysis; D028761:Withholding Treatment / Q000706:statistics & numerical data*