Latent Class Analysis Reveals COVID-19–related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids

Pratik Sinha(Washington University in St. Louis), David Furfaro(Pulmonary and Allergy Associates), Matthew J. Cummings(Pulmonary and Allergy Associates), Darryl Abrams(Pulmonary and Allergy Associates), Kevin Delucchi(Institute of Behavioral Sciences), Manoj V. Maddali, June He(Washington University in St. Louis), Alison Thompson(Pulmonary and Allergy Associates), Michael Murn(Pulmonary and Allergy Associates), John H. Fountain, Amanda Rosen, Shelief Y. Robbins-Juarez(Columbia University), Matthew A. Adan(Columbia University), Tejus Satish(Columbia University), Mahesh V. Madhavan, Aakriti Gupta, Alexander K. Lyashchenko(Columbia University Irving Medical Center), Cara Agerstrand(Pulmonary and Allergy Associates), Natalie Yip(Pulmonary and Allergy Associates), Kristin M. Burkart(Pulmonary and Allergy Associates), Jeremy R. Beitler(Pulmonary and Allergy Associates), Matthew R. Baldwin(Pulmonary and Allergy Associates), Carolyn S. Calfee(University of California, San Francisco), Daniel Brodie(Pulmonary and Allergy Associates), Max R. O’Donnell(Pulmonary and Allergy Associates)
American Journal of Respiratory and Critical Care Medicine
September 20, 2021
Cited by 293Open Access
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Abstract

Abstract Rationale Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus disease (COVID-19) is unknown. Objectives To identify clinically relevant, novel subgroups in COVID-19–related ARDS and compare them with previously described ARDS subphenotypes. Methods Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis was used to identify subgroups with baseline clinical, respiratory, and laboratory data serving as partitioning variables. A previously developed machine learning model was used to classify patients as the hypoinflammatory and hyperinflammatory subphenotypes. Baseline characteristics and clinical outcomes were compared between subgroups. Heterogeneity of treatment effect for corticosteroid use in subgroups was tested. Measurements and Main Results From March 2, 2020, to April 30, 2020, 483 patients with COVID-19–related ARDS met study criteria. A two-class latent class analysis model best fit the population (P = 0.0075). Class 2 (23%) had higher proinflammatory markers, troponin, creatinine, and lactate, lower bicarbonate, and lower blood pressure than class 1 (77%). Ninety-day mortality was higher in class 2 versus class 1 (75% vs. 48%; P < 0.0001). Considerable overlap was observed between these subgroups and ARDS subphenotypes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR cycle threshold was associated with mortality in the hypoinflammatory but not the hyperinflammatory phenotype. Heterogeneity of treatment effect to corticosteroids was observed (P = 0.0295), with improved mortality in the hyperinflammatory phenotype and worse mortality in the hypoinflammatory phenotype, with the caveat that corticosteroid treatment was not randomized. Conclusions We identified two COVID-19–related ARDS subgroups with differential outcomes, similar to previously described ARDS subphenotypes. SARS-CoV-2 PCR cycle threshold had differential value for predicting mortality in the subphenotypes. The subphenotypes had differential treatment responses to corticosteroids.


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