Purpose: To describe the variability and determinants of the effect of extracorporeal CO2 removal (ECCO2R) on tidal volume (Vt), driving pressure (ΔP), and mechanical power (PowerRS) and to determine whether highly responsive patients can be identified for the purpose of predictive enrichment in ECCO2R trial design. Methods: Using data from the SUPERNOVA trial (95 patients with early moderate acute respiratory distress syndrome), the independent effects of alveolar dead space fraction (ADF), respiratory system compliance (Crs), hypoxemia (PaO2/FiO2), and device performance (higher vs lower CO2 extraction) on the magnitude of reduction in Vt, ΔP, and PowerRS permitted by ECCO2R were assessed by linear regression. Predicted and observed changes in ΔP were compared by Bland–Altman analysis. Hypothetical trials of ECCO2R, incorporating predictive enrichment and different target CO2 removal rates, were simulated in the SUPERNOVA study population. Results: Changes in Vt permitted by ECCO2R were independently associated with ADF and device performance but not PaO2/FiO2. Changes in ΔP and PowerRS were independently associated with ADF, Crs, and device performance but not PaO2/FiO2. The change in ΔP predicted from ADF and Crs was moderately correlated with observed change in ΔP (R2 0.32, p < 0.001); limits of agreement between observed and predicted changes in ΔP were ± 3.9 cmH2O. In simulated trials, restricting enrollment to patients with a larger predicted decrease in ΔP enhanced the average reduction in ΔP, increased predicted mortality benefit, and reduced sample size and screening size requirements. The increase in statistical power obtained by restricting enrollment based on predicted ΔP response varied according to device performance as specified by the target CO2 removal rate. Conclusions: The lung-protective benefits of ECCO2R increase with higher alveolar dead space fraction, lower respiratory system compliance, and higher device performance. ADF and Crs, rather than severity of hypoxemia, should be the primary factors determining whether to enroll patients in clinical trials of ECCO2R.
- Acute respiratory distress syndrome
- Artificial ventilation
- Extracorporeal carbon dioxide removal
- Predictive enrichment
- Ventilator-induced lung injury