Patients with acute respiratory distress syndrome (ARDS) caused by COVID-19 have varied responses to recruitment maneuvers and require respiratory assistance with invasive mechanical ventilation. Using latent class analysis (LCA) of imaging and clinical respiratory data, 2 pulmonary subphenotypes with different recruit abilities were found in patients with ARDS unrelated to COVID-19. To that end, researchers intended to determine whether or not COVID-19-related ARDS patients share a common subphenotype. This is a retrospective study of patients on mechanical ventilation who were diagnosed with COVID-19-related ARDS and who underwent CT scans at 10 cmH2O of positive end-expiratory pressure and 20 cmH2O of positive end-expiratory pressure after a recruiting maneuver.
Before recruitment, subphenotypes were identified using LCA applied to quantitative CT-derived data, clinical respiratory parameters, blood gas analyses, and regular laboratory values. There were a total of 99 patients. The best-fit LCA model was found to have a two-class structure, using 12 independent variables. Subphenotype 2 (recruitable) was distinguished from subphenotype 1 by a lower PaO2/FiO2, lower typically aerated lung capacity, and reduced compliance in favor of a higher non-aerated lung mass and a higher mechanical power (non-recruitable). There was no difference in survival (P=0.814), but patients with subphenotype 2 had a greater reduction in non-aerated lung mass in response to a standardized recruitment maneuver (P=0.024) and required longer on mechanical ventilation until successful extubation (adjusted SHR 0.46, 95% CI 0.23-0.91, P=0.026).
In individuals with ARDS caused by COVID-19, investigators discovered 2 separate subphenotypes, recruitable and non-recruitable. These results are consistent with those seen in investigations with ARDS unrelated to COVID-19 and imply that a mixture of imaging and clinical respiratory indicators could aid in identifying recruitable lungs prior to the maneuver.