Predictive Accuracy of COVID-19 World Health Organization (WHO) Severity Classification and Comparison with a Bayesian-Method-Based Severity Score (EPI-SCORE)

Predictive Accuracy of COVID-19 World Health Organization (WHO) Severity Classification and Comparison with a Bayesian-Method-Based Severity Score (EPI-SCORE)

<b>Objectives: </b>Assess the predictive accuracy of the WHO COVID-19 severity classification on COVID-19 hospitalized patients. The secondary aim was to compare its predictive power with a new prediction model, named COVID-19 EPI-SCORE, based on a Bayesian network analysis. <b>Met...

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Bibliographic Details
Main Authors: Christophe de Terwangne, Jabber Laouni, Lionel Jouffe, Jerome R. Lechien, Vincent Bouillon, Sammy Place, Lucio Capulzini, Shahram Machayekhi, Antonia Ceccarelli, Sven Saussez, Antonio Sorgente, On behalf of EPIBASE TEAM
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Pathogens
Subjects:
severity
score
coronavirus
SARS-COV-2
COVID-19
WHO
Online Access:https://www.mdpi.com/2076-0817/9/11/880

Internet

https://www.mdpi.com/2076-0817/9/11/880

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