Analysis of Protein Biomarkers From Hospitalized COVID-19 Patients Reveals Severity-Specific Signatures and Two Distinct Latent Profiles With Differential Responses to Corticosteroids

Philip A. Verhoef, Alexandra B. Spicer, Carlos Lopez-Espina, Akhil Bhargava, Lee Schmalz, Matthew D. Sims, Ashok V. Palagiri, Karthik V. Iyer, Matthew J. Crisp, Alexandra Halalau, Nicholas Maddens, Falgun Gosai, Anwaruddin Syed, Saleem Azad, Aimee Espinosa, Francisco Davila, Hugo Davila, Neil R. Evans, Scott Smith, Bobby ReddyPratik Sinha, Matthew M. Churpek

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1697-1705
Number of pages9
JournalCritical care medicine
Volume51
Issue number12
DOIs
StatePublished - Dec 1 2023

Keywords

  • COVID-19
  • cytokines
  • glucocorticoids
  • heterogenous treatment effects
  • latent profile analysis

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