Prospective Assessment of the Feasibility of a Trial of Low-Tidal Volume Ventilation for Patients with Acute Respiratory Failure.

RATIONALE: Low-tidal volume ventilation (LTVV; 6 ml/kg) benefits patients with acute respiratory distress syndrome and may aid those with other causes of respiratory failure. Current early ventilation practices are poorly defined.

OBJECTIVES: We observed patients with acute respiratory failure to assess the feasibility of a pragmatic trial of LTVV and to guide experimental design.

METHODS: We prospectively enrolled consecutive patients with acute respiratory failure admitted to intensive care units expected to participate in the proposed trial. We collected clinical data as well as information on initial and daily ventilator settings and inpatient mortality. We estimated the benefit of LTVV using predictive linear and nonlinear models. We simulated models to estimate power and feasibility of a cluster-randomized trial of LTVV versus usual care in acute respiratory failure.

RESULTS: We included 2,484 newly mechanically ventilated patients (31% with acute respiratory distress syndrome) from 49 hospitals. Hospital mortality was 28%. Mean initial tidal volume was 7.1 ml/kg predicted body weight (95% confidence interval, 7.1-7.2), with 78% of patients receiving tidal volumes less than or equal to 8 ml/kg. Our models estimated a mortality benefit of 0-2% from LTVV compared with usual care. Simulation of a stepped-wedged cluster-randomized trial suggested that enrollment of 106,361 patients would be necessary to achieve greater than 90% power.

CONCLUSIONS: Use of initial tidal volumes less than 8 ml/kg predicted body weight was common at hospitals participating in the National Heart, Lung, and Blood Institute Prevention and Early Treatment of Acute Lung Injury (PETAL) Network. After considering the size and budgetary requirement for a cluster-randomized trial of LTVV versus usual care in acute respiratory failure, the PETAL Network deemed the proposed trial infeasible. A rapid observational study and simulations to model anticipated power may help better design trials.