Severity and mortality prediction models to triage Indian COVID-19 patients.

Autor:	Bhatia S; Department of Chemical engineering, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, India., Makhija Y; Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, India., Jayaswal S; CMC Ludhiana, Ludhiana, Punjab, India., Singh S; Department of Anaesthesiology and Critical Care, AFMC, Pune, Maharashtra, India., Malik PS; Department of Medical Oncology, All India Institute of Medical Sciences, New Delhi, India., Venigalla SK; Department of Anaesthesiology and Critical Care, AFMC, Pune, Maharashtra, India., Gupta P; Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, India., Samaga SN; Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, India., Hota RN; Department of Anaesthesiology and Critical Care, AFMC, Pune, Maharashtra, India., Gupta I; Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, India.
Jazyk:	angličtina
Zdroj:	PLOS digital health [PLOS Digit Health] 2022 Mar 09; Vol. 1 (3), pp. e0000020. Date of Electronic Publication: 2022 Mar 09 (Print Publication: 2022).
DOI:	10.1371/journal.pdig.0000020
Abstrakt:	As the second wave in India mitigates, COVID-19 has now infected about 29 million patients countrywide, leading to more than 350 thousand people dead. As the infections surged, the strain on the medical infrastructure in the country became apparent. While the country vaccinates its population, opening up the economy may lead to an increase in infection rates. In this scenario, it is essential to effectively utilize the limited hospital resources by an informed patient triaging system based on clinical parameters. Here, we present two interpretable machine learning models predicting the clinical outcomes, severity, and mortality, of the patients based on routine non-invasive surveillance of blood parameters from one of the largest cohorts of Indian patients at the day of admission. Patient severity and mortality prediction models achieved 86.3% and 88.06% accuracy, respectively, with an AUC-ROC of 0.91 and 0.92. We have integrated both the models in a user-friendly web app calculator, https://triage-COVID-19.herokuapp.com/, to showcase the potential deployment of such efforts at scale. Competing Interests: The authors have declared that no competing interests exist. (Copyright: © 2022 Bhatia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze:	MEDLINE
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