Latent Class Analysis Reveals COVID-19–related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids
| Autor: | Jeremy R. Beitler, Shelief Y Robbins-Juarez, Kevin L. Delucchi, Matthew J. Cummings, Kristin M. Burkart, Darryl Abrams, Daniel Brodie, Pratik Sinha, Natalie H Yip, Cara Agerstrand, Manoj V Maddali, June He, Carolyn S. Calfee, Alex K. Lyashchenko, Alison Thompson, John Fountain, Mahesh V. Madhavan, Tejus Satish, David Furfaro, Michael Murn, Max R. O'Donnell, Amanda Rosen, Matthew A Adan, Matthew R. Baldwin, Aakriti Gupta |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Pulmonary and Respiratory Medicine ARDS medicine.medical_specialty phenotyping Coronavirus disease 2019 (COVID-19) Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Respiratory System Population Columbia university Critical Care and Intensive Care Medicine Medical and Health Sciences Positive-Pressure Respiration Cohort Studies chemistry.chemical_compound Rare Diseases Adrenal Cortex Hormones Internal medicine latent class analysis medicine Humans education Acute Respiratory Distress Syndrome Lung Retrospective Studies Aged Respiratory Distress Syndrome Creatinine education.field_of_study biology SARS-CoV-2 business.industry COVID-19 Original Articles Middle Aged medicine.disease Troponin Latent class model COVID-19 Drug Treatment Infectious Diseases Emerging Infectious Diseases Good Health and Well Being chemistry Latent Class Analysis biology.protein Female business COVID-19/Critical Care |
| Zdroj: | American journal of respiratory and critical care medicine, vol 204, iss 11 American Journal of Respiratory and Critical Care Medicine |
| ISSN: | 1535-4970 1073-449X |
| DOI: | 10.1164/rccm.202105-1302oc |
| Popis: | Rationale Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with COVID-19 is unknown. The objective of this study was to identify clinically relevant, novel subgroups in COVID-19-related ARDS, and compare them to previously described ARDS subphenotypes. Methods Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis (LCA) 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 (HTE) for corticosteroid-use in subgroups was tested. Measurements and Main Results From 3/2-4/30/2020, 483 patients with COVID-19-related ARDS met study criteria. A two-class LCA model best fit the population (p=0.0075). Class 2 (23%) had higher pro-inflammatory markers, troponin, creatinine and lactate, lower bicarbonate and lower blood pressure than Class 1 (77%). 90-day mortality was higher in Class 2 versus Class 1 (75% vs 48%; p |
| Databáze: | OpenAIRE |
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