Abstract and Introduction
Abstract
Introduction: Prediction of death and prolonged mechanical ventilation is important in terms of projecting resource utilization and in establishing protocols for clinical studies of acute lung injury (ALI). We aimed to identify risk factors for a combined end-point of death and/or prolonged ventilator dependence and developed an ALI-specific prediction model.
Methods: In this retrospective analysis of three multicenter clinical studies, we identified predictors of death or ventilator dependence from variables prospectively recorded during the first three days of mechanical ventilation. After the prediction model was derived in an international cohort of patients with ALI, it was validated in two independent samples of patients enrolled in a clinical trial involving 17 academic centers and a North American population-based cohort.
Results: A combined end-point of death and/or ventilator dependence at 14 days or later occurred in 68% of patients in the international cohort, 60% of patients in the clinical trial, and 59% of patients in the population-based cohort. In the derivation cohort, a model based on age, oxygenation index on day 3, and cardiovascular failure on day 3 predicted death and/or ventilator dependence. The prediction model performed better in the clinical trial validation cohort (area under the receiver operating curve 0.81, 95% confidence interval 0.77 to 0.84) than in the population-based validation cohort (0.71, 95% confidence interval 0.65 to 0.76).
Conclusion: A model based on age and cardiopulmonary function three days after the intubation is able to predict, moderately well, a combined end-point of death and/or prolonged mechanical ventilation in patients with ALI.
Introduction
Although a significant number of patients with acute lung injury (ALI) die or require prolonged mechanical ventilation, the tools for predicting mortality and morbidity in this group of patients are limited. Parameters related to the degree of impairment in pulmonary function and nonpulmonary organ failures have been associated with increased mortality and prolonged mechanical ventilation in patients with ALI, and in mechanically ventilated patients in general. Compared with values collected on day 1, evolution of the disease and response to treatment during the first three days of mechanical ventilation provide valuable prognostic information.
The present study analyzed potential predictors of outcome from mechanical ventilation in patients with ALI in three recent prospective cohorts with the following specific aims: to identify risk factors for death and/or ventilator dependence; to develop an ALI-specific prediction model; and to validate the prediction model in independent samples from both population-based and clinical trial databases, in order to determine the potential value of the model for clinical decision making and clinical trial design in patients who are likely to die or require prolonged mechanical ventilation.