Differential Effect of Positive End-Expiratory Pressure Strategies in Patients With ARDS: A Bayesian Analysis of Clinical Subphenotypes.

backgroundARDS is a heterogeneous condition with two subphenotypes identified by different methodologies. Our group similarly identified two ARDS subphenotypes using nine routinely available clinical variables. However, whether these are associated with differential response to treatment has yet to be explored. RESEARCH QUESTION: Are there differential responses to positive end-expiratory pressure (PEEP) strategies on 28-day mortality according to subphenotypes in adult patients with ARDS? STUDY DESIGN AND

methodsWe evaluated data from two prior ARDS trials (Higher vs Lower Positive End-Expiratory Pressures in Patients With the ARDS [ALVEOLI] and the Alveolar Recruitment in ARDS Trial [ART]) that compared different PEEP strategies. We classified patients into one of two subphenotypes as described previously. We assessed the differential effect of PEEP with a Bayesian hierarchical logistic model for the primary outcome of 28-day mortality.

resultsWe analyzed data from 1,559 patients with ARDS. Compared with lower PEEP, a higher PEEP strategy resulted in higher 28-day mortality in patients with subphenotype A disease in the ALVEOLI study (OR, 1.61; 95% credible interval [CrI], 0.90-2.94) and ART (OR, 1.73; 95% CrI, 1.01-2.98), with a probability of harm resulting from higher PEEP in this subphenotype of 94.3% and 97.7% in the ALVEOLI and ART studies, respectively. Higher PEEP was not associated with mortality in patients with subphenotype B disease in each trial (OR, 0.95 [95% CrI, 0.51-1.73] and 1.00 [95% CrI, 0.63-1.55], respectively), with probability of benefit of 56.4% and 50.7% in the ALVEOLI and ART studies, respectively. These effects were not modified by Pao

interpretationWe found evidence of differential response to PEEP strategies across two ARDS subphenotypes, suggesting possible harm with a higher PEEP strategy in one subphenotype. These observations may assist with predictive enrichment in future clinical trials.