Temporal stability of inflammatory subphenotypes of acute respiratory distress syndrome: 28-day insights from the ICAR trial
Year: 2025
Type: article
Abstract: BACKGROUND: International guidelines have emphasized the necessity of evaluating the temporal stability of acute respiratory distress syndrome (ARDS) subphenotypes. This study aimed to assess the temporal stability of subphenotypes of ARDS over 28 days. METHODS: A reanalysis of a randomized trial was conducted, including patients with COVID-19-related moderate-to-severe ARDS across 43 centers. A K-means clustering was conducted to identify subphenotypes at 7-day intervals from inclusion to day 28. A Bayesian discrete-time Markov model was constructed to assess the temporal stability of subphenotypes. RESULTS: Two subphenotypes were identified among 146 patients. At inclusion, 121 (83%) patients were in the hypoinflammatory subphenotype and 25 (17%) in the hyperinflammatory subphenotype. The hyperinflammatory subphenotype was associated with higher rates of organ failure, higher plasma levels of cytokines, chemokines, adhesion molecules, and proangiogenic factors, and lower endothelial stability than the hypoinflammatory subphenotype. The hyperinflammatory subphenotype was associated with higher 28-day mortality (13/25, 52% vs. 30/121, 25%, p = 0.001) and fewer ventilatory-free-days through day 28 (p < 0.01) than the hypoinflammatory subphenotype. In the Bayesian Markov model, over 7-day intervals, patients in the hypoinflammatory subphenotype had a higher probability of remaining hypoinflammatory (70%) or being extubated (17%) than of progressing to the hyperinflammatory subphenotype (7%). Inversely, patients in the hyperinflammatory subphenotype had a higher probability of remaining in the hyperinflammatory subphenotype (52%) or dying (23%) than of transitioning to the hypoinflammatory subphenotype (20%) or being extubated (5%). CONCLUSIONS: Inflammatory subphenotypes were stable in COVID-19-related ARDS, with few transitions over 28 days. Monitoring these subphenotypes could be valuable for assessing patient trajectories and treatment responses.
Institutions: Centre National de la Recherche Scientifique, Inserm, Université Clermont Auvergne, Université Paris Cité, Centre Hospitalier Universitaire de Clermont-Ferrand, Institut Génétique, Reproduction et Développement, Beth Israel Deaconess Medical Center, Institut national de recherche en sciences et technologies du numérique, Université de Montpellier, Institut Cochin, Hôpital Cochin, GHU Paris psychiatrie & neurosciences, Harvard University, Düsseldorf University Hospital, Heinrich Heine University Düsseldorf, Physiologie et Médecine Expérimentale du Coeur et des Muscles, Centre Hospitalier Universitaire de Montpellier, Hôpital Arnaud de Villeneuve, Institut Pasteur, Hôpital Saint Eloi
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,050
Award: G8768336817
OpenAlex ID: W4410759221