Hospital trajectories and early predictors of clinical outcomes differ between SARS-CoV-2 and influenza pneumonia

• Type of Material: Article
• Authors: Patrick G Lyons, Washington University School of Medicine; Sivasubramanium V. Bhavani, Emory University; Aaloke Mody, Washington University, St. Louis; Alice Bewley, Washington University, St. Louis; Katherine Dittman, Washington University, St. Louis; Aisling Doyle, Washington University, St. Louis; Samuel L Windham, Washington University, St. Louis; Tej M Patel, Washington University, St. Louis; Bharat N Raju, Washington University, St. Louis; Matthew Keller, Washington University, St. Louis; Matthew M Churpek, University of Wisconsin, Madison; Carolyn S Calfee, University of California San Francisco; Andrew P Michelson, Washington University in St. Louis; Thomas Kannampallil, Washington University in St. Louis; Elvin H Geng, Washington University in St. Louis; Pratik Sinha, Washington University in St. Louis
• Language: English
• Date: 2022-11-01
• Publisher: ELSEVIER
• Publication Version: Final Published Version
• Copyright Statement: © 2022 The Author(s)
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.ebiom.2022.104295
• Title of Journal or Parent Work: EBIOMEDICINE
• Volume: 85
• Start Page: 104295
• End Page: 104295
• Keywords: COVID-19; Research & Experimental Medicine; General & Internal Medicine; Medicine, Research & Experimental; Life Sciences & Biomedicine; Influenza; Viral pneumonia; Statistical modelling; SARS-CoV-2; Science & Technology; Medicine, General & Internal; Hospital outcomes; CORONAVIRUS DISEASE 2019
• Research Categories: Health Sciences, Medicine and Surgery

Abstract

Background: A comparison of pneumonias due to SARS-CoV-2 and influenza, in terms of clinical course and predictors of outcomes, might inform prognosis and resource management. We aimed to compare clinical course and outcome predictors in SARS-CoV-2 and influenza pneumonia using multi-state modelling and supervised machine learning on clinical data among hospitalised patients. Methods: This multicenter retrospective cohort study of patients hospitalised with SARS-CoV-2 (March-December 2020) or influenza (Jan 2015-March 2020) pneumonia had the composite of hospital mortality and hospice discharge as the primary outcome. Multi-state models compared differences in oxygenation/ventilatory utilisation between pneumonias longitudinally throughout hospitalisation. Differences in predictors of outcome were modelled using supervised machine learning classifiers. Findings: Among 2,529 hospitalisations with SARS-CoV-2 and 2,256 with influenza pneumonia, the primary outcome occurred in 21% and 9%, respectively. Multi-state models differentiated oxygen requirement progression between viruses, with SARS-CoV-2 manifesting rapidly-escalating early hypoxemia. Highly contributory classifier variables for the primary outcome differed substantially between viruses. Interpretation: SARS-CoV-2 and influenza pneumonia differ in presentation, hospital course, and outcome predictors. These pathogen-specific differential responses in viral pneumonias suggest distinct management approaches should be investigated. Funding: This project was supported by NIH/NCATS UL1 TR002345, NIH/NCATS KL2 TR002346 (PGL), the Doris Duke Charitable Foundation grant 2015215 (PGL), NIH/NHLBI R35 HL140026 (CSC), and a Big Ideas Award from the BJC HealthCare and Washington University School of Medicine Healthcare Innovation Lab and NIH/NIGMS R35 GM142992 (PS).