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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
A multicenter mortality prediction model for patients receiving prolonged mechanical ventilation
Critical Care Medicine, Volume 40, No. 4, Year 2012
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Description
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. Design: Cohort study. Setting: Five geographically diverse tertiary care medical centers in the United States (California, Colorado, North Carolina, Pennsylvania, and Washington). Patients: Two hundred sixty adult patients who received at least 21 days of mechanical ventilation after acute illness. Interventions: None. Measurements and Main 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%. Conclusion: 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. © 2012 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins.
Authors & Co-Authors
Carson, Shannon S.
United States, Chapel Hill
The University of North Carolina at Chapel Hill
Kahn, Jeremy M.
Unknown Affiliation
Hough, Catherine L.
United States, Seattle
University of Washington
Douglas, Ivor S.
United States, Denver
Denver Health Med Center
Bangdiwala, Shrikant I.
United States, Chapel Hill
The University of North Carolina at Chapel Hill
Rubenfeld, Gordon David
Canada, Toronto
University of Toronto
Statistics
Citations: 117
Authors: 6
Affiliations: 7
Identifiers
Doi:
10.1097/CCM.0b013e3182387d43
ISSN:
15300293
Research Areas
Health System And Policy
Study Design
Cohort Study
Study Approach
Quantitative