TY - JOUR
T1 - Analysis of Protein Biomarkers From Hospitalized COVID-19 Patients Reveals Severity-Specific Signatures and Two Distinct Latent Profiles With Differential Responses to Corticosteroids
AU - Verhoef, Philip A.
AU - Spicer, Alexandra B.
AU - Lopez-Espina, Carlos
AU - Bhargava, Akhil
AU - Schmalz, Lee
AU - Sims, Matthew D.
AU - Palagiri, Ashok V.
AU - Iyer, Karthik V.
AU - Crisp, Matthew J.
AU - Halalau, Alexandra
AU - Maddens, Nicholas
AU - Gosai, Falgun
AU - Syed, Anwaruddin
AU - Azad, Saleem
AU - Espinosa, Aimee
AU - Davila, Francisco
AU - Davila, Hugo
AU - Evans, Neil R.
AU - Smith, Scott
AU - Reddy, Bobby
AU - Sinha, Pratik
AU - Churpek, Matthew M.
N1 - Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - OBJECTIVES: To identify and validate novel COVID-19 subphenotypes with potential heterogenous treatment effects (HTEs) using electronic health record (EHR) data and 33 unique biomarkers. DESIGN: Retrospective cohort study of adults presenting for acute care, with analysis of biomarkers from residual blood collected during routine clinical care. Latent profile analysis (LPA) of biomarker and EHR data identified subphenotypes of COVID-19 inpatients, which were validated using a separate cohort of patients. HTE for glucocorticoid use among subphenotypes was evaluated using both an adjusted logistic regression model and propensity matching analysis for in-hospital mortality. SETTING: Emergency departments from four medical centers. PATIENTS: Patients diagnosed with COVID-19 based on International Classification of Diseases, 10th Revision codes and laboratory test results. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Biomarker levels generally paralleled illness severity, with higher levels among more severely ill patients. LPA of 522 COVID-19 inpatients from three sites identified two profiles: profile 1 (n = 332), with higher levels of albumin and bicarbonate, and profile 2 (n = 190), with higher inflammatory markers. Profile 2 patients had higher median length of stay (7.4 vs 4.1 d; p < 0.001) and in-hospital mortality compared with profile 1 patients (25.8% vs 4.8%; p < 0.001). These were validated in a separate, single-site cohort (n = 192), which demonstrated similar outcome differences. HTE was observed (p = 0.03), with glucocorticoid treatment associated with increased mortality for profile 1 patients (odds ratio = 4.54). CONCLUSIONS: In this multicenter study combining EHR data with research biomarker analysis of patients with COVID-19, we identified novel profiles with divergent clinical outcomes and differential treatment responses.
AB - OBJECTIVES: To identify and validate novel COVID-19 subphenotypes with potential heterogenous treatment effects (HTEs) using electronic health record (EHR) data and 33 unique biomarkers. DESIGN: Retrospective cohort study of adults presenting for acute care, with analysis of biomarkers from residual blood collected during routine clinical care. Latent profile analysis (LPA) of biomarker and EHR data identified subphenotypes of COVID-19 inpatients, which were validated using a separate cohort of patients. HTE for glucocorticoid use among subphenotypes was evaluated using both an adjusted logistic regression model and propensity matching analysis for in-hospital mortality. SETTING: Emergency departments from four medical centers. PATIENTS: Patients diagnosed with COVID-19 based on International Classification of Diseases, 10th Revision codes and laboratory test results. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Biomarker levels generally paralleled illness severity, with higher levels among more severely ill patients. LPA of 522 COVID-19 inpatients from three sites identified two profiles: profile 1 (n = 332), with higher levels of albumin and bicarbonate, and profile 2 (n = 190), with higher inflammatory markers. Profile 2 patients had higher median length of stay (7.4 vs 4.1 d; p < 0.001) and in-hospital mortality compared with profile 1 patients (25.8% vs 4.8%; p < 0.001). These were validated in a separate, single-site cohort (n = 192), which demonstrated similar outcome differences. HTE was observed (p = 0.03), with glucocorticoid treatment associated with increased mortality for profile 1 patients (odds ratio = 4.54). CONCLUSIONS: In this multicenter study combining EHR data with research biomarker analysis of patients with COVID-19, we identified novel profiles with divergent clinical outcomes and differential treatment responses.
KW - COVID-19
KW - cytokines
KW - glucocorticoids
KW - heterogenous treatment effects
KW - latent profile analysis
UR - http://www.scopus.com/inward/record.url?scp=85177103853&partnerID=8YFLogxK
U2 - 10.1097/CCM.0000000000005983
DO - 10.1097/CCM.0000000000005983
M3 - Article
C2 - 37378460
AN - SCOPUS:85177103853
SN - 0090-3493
VL - 51
SP - 1697
EP - 1705
JO - Critical care medicine
JF - Critical care medicine
IS - 12
ER -