ABSTRACT
Introduction: Patients with COVID-19-related acute respiratory distress syndrome (ARDS) require respiratory support with invasive mechanical ventilation and show varying responses to recruitment manoeuvres. In patients with ARDS not related to COVID-19, two pulmonary subphenotypes that differed in recruitability were identified using latent class analysis (LCA) of imaging and clinical respiratory parameters [1]. We aimed to validate these phenotypes and evaluate if similar subphenotypes are present in patients with COVID-19-related ARDS. Method(s): This is the retrospective analysis of mechanically ventilated patients with COVID-19-related ARDS who underwent CT scans at positive end-expiratory pressure of 10 cmH2O and after a recruitment manoeuvre at 20 cmH2O. LCA was applied to quantitative CT-derived parameters, clinical respiratory parameters, blood gas analysis and routine laboratory values before recruitment to identify subphenotypes. Result(s): 99 patients were included. Using 12 variables, a two-class LCA model was identified as best fitting. Subphenotype 2 (recruitable) was characterized by a lower PaO2/ FiO2, lower normally aerated lung volume and lower compliance as opposed to a higher nonaerated lung mass and higher mechanical power when compared to subphenotype 1 (non-recruitable) (Fig. 1). Patients with subphenotype 2 had more decrease in non-aerated lung mass in response to a standardized recruitment manoeuvre (p = 0.024) and were mechanically ventilated longer until successful extubation (adjusted SHR 0.46, 95% CI 0.23-0.91, p = 0.026), while no difference in survival was found (p = 0.814). Conclusion(s): A recruitable and non-recruitable subphenotype were identified in patients with COVID-19-related ARDS. The subphenotypes are similar to non-COVID-19-related ARDS and are promising for identification of recruitable patients in future practice as they can be classified with only few clinically available parameters before the recruitment manoeuvre.