title: Attributable mortality of ventilator-associated pneumonia: a reappraisal using causal analysis.
abstract: BACKGROUND
  Measuring the attributable mortality of ventilator-associated pneumonia (VAP) is challenging and prone to different forms of bias. Studies addressing this issue have produced variable and controversial results.
  
  
  OBJECTIVE
  We estimate the attributable mortality of VAP in a large multicenter cohort using statistical methods from the field of causal inference.
  
  
  METHODS
  Patients (n = 4,479) from the longitudinal prospective (1997-2008) French multicenter Outcomerea database were included if they stayed in the intensive care unit (ICU) for at least 2 days and received mechanical ventilation (MV) within 48 hours after ICU admission. A competing risk survival analysis, treating ICU discharge as a competing risk for ICU mortality, was conducted using a marginal structural modeling approach to adjust for time-varying confounding by disease severity.
  
  
  RESULTS
  Six hundred eighty-five (15.3%) patients acquired at least one episode of VAP. We estimated that 4.4% (95% confidence interval, 1.6-7.0%) of the deaths in the ICU on Day 30 and 5.9% (95% confidence interval, 2.5-9.1%) on Day 60 are attributable to VAP. With an observed ICU mortality of 23.3% on Day 30 and 25.6% on Day 60, this corresponds to an ICU mortality attributable to VAP of about 1% on Day 30 and 1.5% on Day 60.
  
  
  CONCLUSIONS
  Our study on the attributable mortality of VAP is the first that simultaneously accounts for the time of acquiring VAP, informative loss to follow-up after ICU discharge, and the existence of complex feedback relations between VAP and the evolution of disease severity. In contrast to the majority of previous reports, we detected a relatively limited attributable ICU mortality of VAP.
authors.affiliation: Department of Applied Mathematics and Computer Sciences, Ghent University, Ghent, Belgium. maarten.bekaert@ugent.be
authors.forename: Maarten
authors.initials: M
authors.lastname: Bekaert
authors.forename: Jean-Francois
authors.initials: JF
authors.lastname: Timsit
authors.forename: Stijn
authors.initials: S
authors.lastname: Vansteelandt
authors.forename: Pieter
authors.initials: P
authors.lastname: Depuydt
authors.forename: Aurélien
authors.initials: A
authors.lastname: Vésin
authors.forename: Maité
authors.initials: M
authors.lastname: Garrouste-Orgeas
authors.forename: Johan
authors.initials: J
authors.lastname: Decruyenaere
authors.forename: Christophe
authors.initials: C
authors.lastname: Clec'h
authors.forename: Elie
authors.initials: E
authors.lastname: Azoulay
authors.forename: Dominique
authors.initials: D
authors.lastname: Benoit
mesh_terms: D000890:Anti-Infective Agents / Q000627:therapeutic use; D015984:Causality; D003428:Cross Infection / Q000401:mortality; D005260:Female; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D053717:Pneumonia, Ventilator-Associated / Q000188:drug therapy / Q000209:etiology / Q000382:microbiology / Q000401:mortality*; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D016019:Survival Analysis
chemical_list: D000890:Anti-Infective Agents