title: A multicenter mortality prediction model for patients receiving prolonged mechanical ventilation.
abstract: OBJECTIVE
  Significant deficiencies exist in the communication of prognosis for patients requiring prolonged mechanical ventilation after acute illness, in part because of clinician uncertainty about long-term outcomes. We sought to refine a mortality prediction model for patients requiring prolonged ventilation using a multicentered study design.
  
  
  METHODS
  Cohort study.
  
  
  METHODS
  Five geographically diverse tertiary care medical centers in the United States (California, Colorado, North Carolina, Pennsylvania, and Washington).
  
  
  METHODS
  Two hundred sixty adult patients who received at least 21 days of mechanical ventilation after acute illness.
  
  
  METHODS
  None.
  
  
  RESULTS
  For the probability model, we included age, platelet count, and requirement for vasopressors and/or hemodialysis, each measured on day 21 of mechanical ventilation, in a logistic regression model with 1-yr mortality as the outcome variable. We subsequently modified a simplified prognostic scoring rule (ProVent score) by categorizing the risk variables (age 18-49, 50-64, and ≥65 yrs; platelet count 0-150 and >150; vasopressors; hemodialysis) in another logistic regression model and assigning points to variables according to β coefficient values. Overall mortality at 1 yr was 48%. The area under the curve of the receiver operator characteristic curve for the primary ProVent probability model was 0.79 (95% confidence interval 0.75-0.81), and the p value for the Hosmer-Lemeshow goodness-of-fit statistic was .89. The area under the curve for the categorical model was 0.77, and the p value for the goodness-of-fit statistic was .34. The area under the curve for the ProVent score was 0.76, and the p value for the Hosmer-Lemeshow goodness-of-fit statistic was .60. For the 50 patients with a ProVent score >2, only one patient was able to be discharged directly home, and 1-yr mortality was 86%.
  
  
  CONCLUSIONS
  The ProVent probability model is a simple and reproducible model that can accurately identify patients requiring prolonged mechanical ventilation who are at high risk of 1-yr mortality.
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Cecil B. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, NC, USA. scarson@med.unc.edu
authors.forename: Shannon S
authors.initials: SS
authors.lastname: Carson
authors.forename: Jeremy M
authors.initials: JM
authors.lastname: Kahn
authors.forename: Catherine L
authors.initials: CL
authors.lastname: Hough
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Seeley
authors.forename: Douglas B
authors.initials: DB
authors.lastname: White
authors.forename: Ivor S
authors.initials: IS
authors.lastname: Douglas
authors.forename: Christopher E
authors.initials: CE
authors.lastname: Cox
authors.forename: Ellen
authors.initials: E
authors.lastname: Caldwell
authors.forename: Shrikant I
authors.initials: SI
authors.lastname: Bangdiwala
authors.forename: Joanne M
authors.initials: JM
authors.lastname: Garrett
authors.forename: Gordon D
authors.initials: GD
authors.lastname: Rubenfeld
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003422:Critical Care / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010976:Platelet Count; D006435:Renal Dialysis; D012121:Respiration, Artificial / Q000401:mortality*; D012189:Retrospective Studies; D012307:Risk Factors; D014662:Vasoconstrictor Agents / Q000627:therapeutic use; D055815:Young Adult
chemical_list: D014662:Vasoconstrictor Agents
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