• Catherine L Hough, Ellen S Caldwell, Christopher E Cox, Ivor S Douglas, Jeremy M Kahn, Douglas B White, Eric J Seeley, Shrikant I Bangdiwala, Gordon D Rubenfeld, Derek C Angus, Shannon S Carson, and ProVent Investigators and the National Heart Lung and Blood Institute’s Acute Respiratory Distress Syndrome Network.
• 1Division of Pulmonary and Critical Care Medicine, Harborview Medical Center, University of Washington School of Medicine, Seattle, WA. 2Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University School of Medicine, Durham, NC. 3Division of Pulmonary and Critical Care Medicine, University of Colorado School of Medicine, Denver, CO. 4Clinical Research, Investigation and Systems Modeling of Acute Illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA. 5Division of Pulmonary and Critical Care Medicine, University of California, San Francisco School of Medicine, San Francisco, CA. 6Cecil B. Sheps Center for Health Services Research and Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina, Chapel Hill, NC. 7Trauma, Emergency, and Critical Care Program, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada.
• Crit. Care Med. 2015 Nov 1; 43 (11): 2339-45.

ObjectivesThe existing risk prediction model for patients requiring prolonged mechanical ventilation is not applicable until after 21 days of mechanical ventilation. We sought to develop and validate a mortality prediction model for patients earlier in the ICU course using data from day 14 of mechanical ventilation.DesignMulticenter retrospective cohort study.SettingForty medical centers across the United States.PatientsAdult patients receiving at least 14 days of mechanical ventilation.InterventionsNone.Measurements And Main ResultsPredictor variables were measured on day 14 of mechanical ventilation in the development cohort and included in a logistic regression model with 1-year mortality as the outcome. Variables were sequentially eliminated to develop the ProVent 14 model. This model was then generated in the validation cohort. A simplified prognostic scoring rule (ProVent 14 Score) using categorical variables was created in the development cohort and then tested in the validation cohort. Model discrimination was assessed by the area under the receiver operator characteristic curve. Four hundred ninety-one patients and 245 patients were included in the development and validation cohorts, respectively. The most parsimonious model included age, platelet count, requirement for vasopressors, requirement for hemodialysis, and nontrauma admission. The area under the receiver operator characteristic curve for the ProVent 14 model using continuous variables was 0.80 (95% CI, 0.76-0.83) in the development cohort and 0.78 (95% CI, 0.72-0.83) in the validation cohort. The ProVent 14 Score categorized age at 50 and 65 years old and platelet count at 100×10(9)/L and had similar discrimination as the ProVent 14 model in both cohorts.ConclusionUsing clinical variables available on day 14 of mechanical ventilation, the ProVent 14 model can identify patients receiving prolonged mechanical ventilation with a high risk of mortality within 1 year.

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