Prediction models for COVID-19 clinical decision making

Artuur M Leeuwenberg,Ewoud Schuit

doi:10.1016/s2589-7500(20)30226-0

Artuur M Leeuwenberg, Ewoud Schuit

Open Access

https://doi.org/10.1016/s2589-7500(20)30226-0

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Abstract

Prediction models for COVID-19 clinical decision making

Highlights

As of Sept 2, 2020, more than 25 million cases of COVID-19 have been reported, with more than 850 000 associated deaths worldwide
Prediction models that combine patient and disease characteristics to estimate the risk of a poor outcome from COVID-19 can provide helpful assistance in clinical decision making.[2]
In The Lancet Digital Health, Arjun S Yadaw and colleagues present two models to predict mortality in patients with COVID-19 admitted to the Mount Sinai Health System in the New York city area.[4]

Summary

Introduction

As of Sept 2, 2020, more than 25 million cases of COVID-19 have been reported, with more than 850 000 associated deaths worldwide. This disease is a major burden on health-care systems, leading to difficult decisions about who to treat and who not to.[1] Prediction models that combine patient and disease characteristics to estimate the risk of a poor outcome from COVID-19 can provide helpful assistance in clinical decision making.[2]

Results

Conclusion