A measure that identifies patients who are at high risk of mortality after prolonged ventilation will help physicians communicate prognoses to patients or surrogate decision makers. Our objective was to develop and validate a prognostic model for 1-yr mortality in patients ventilated for 21 days or more.
The authors conducted a prospective cohort study.
The study took place at a university-based tertiary care hospital.
Three hundred consecutive medical, surgical, and trauma patients requiring mechanical ventilation for at least 21 days were prospectively enrolled.
Predictive variables were measured on day 21 of ventilation for the first 200 patients and entered into logistic regression models with 1-yr and 3-mo mortality as outcomes. Final models were validated using data from 100 subsequent patients. One-year mortality was 51% in the development set and 58% in the validation set. Independent predictors of mortality included requirement for vasopressors, hemodialysis, platelet count ≤150 × 109/L, and age ≥50 yrs. Areas under the receiver operating characteristic curve for the development model and validation model were .82 (se .03) and .82 (se .05), respectively. The model had sensitivity of .42 (se .12) and specificity of .99 (se .01) for identifying patients who had ≥90% risk of death at 1 yr. Observed mortality was highly consistent with both 3- and 12-mo predicted mortality. These four predictive variables can be used in a simple prognostic score that clearly identifies low-risk patients (no risk factors, 15% mortality) and high-risk patients (three or four risk factors, 97% mortality).
Simple clinical variables measured on day 21 of mechanical ventilation can identify patients at highest and lowest risk of death from prolonged ventilation.
From the Department of Medicine (SSC, JG, LCH, JL, TSC), University of North Carolina School of Medicine, Chapel Hill, NC; the Department of Medicine (JG, CEC), Duke University School of Medicine; and the Department of Medicine (MCB, DLL), East Carolina School of Medicine.
Supported by National Institutes of Health grants K23 HL067068 (SSC) and K23 HL081048 (CEC).
The authors have not disclosed any potential conflicts of interest.
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