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01-12-2022 | SARS-CoV-2 | Research

Predicting progression to severe COVID-19 using the PAINT score

Authors: Ming Wang, Dongbo Wu, Chang-Hai Liu, Yan Li, Jianghong Hu, Wei Wang, Wei Jiang, Qifan Zhang, Zhixin Huang, Lang Bai, Hong Tang

Published in: BMC Infectious Diseases | Issue 1/2022

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Abstract

Objectives

One of the major challenges in treating patients with coronavirus disease 2019 (COVID-19) is predicting the severity of disease. We aimed to develop a new score for predicting progression from mild/moderate to severe COVID-19.

Methods

A total of 239 hospitalized patients with COVID-19 from two medical centers in China between February 6 and April 6, 2020 were retrospectively included. The prognostic abilities of variables, including clinical data and laboratory findings from the electronic medical records of each hospital, were analysed using the Cox proportional hazards model and Kaplan–Meier methods. A prognostic score was developed to predict progression from mild/moderate to severe COVID-19.

Results

Among the 239 patients, 216 (90.38%) patients had mild/moderate disease, and 23 (9.62%) progressed to severe disease. After adjusting for multiple confounding factors, pulmonary disease, age > 75, IgM, CD16+/CD56+ NK cells and aspartate aminotransferase were independent predictors of progression to severe COVID-19. Based on these five factors, a new predictive score (the ‘PAINT score’) was established and showed a high predictive value (C-index = 0.91, 0.902 ± 0.021, p < 0.001). The PAINT score was validated using a nomogram, bootstrap analysis, calibration curves, decision curves and clinical impact curves, all of which confirmed its high predictive value.

Conclusions

The PAINT score for progression from mild/moderate to severe COVID-19 may be helpful in identifying patients at high risk of progression.
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Metadata
Title
Predicting progression to severe COVID-19 using the PAINT score
Authors
Ming Wang
Dongbo Wu
Chang-Hai Liu
Yan Li
Jianghong Hu
Wei Wang
Wei Jiang
Qifan Zhang
Zhixin Huang
Lang Bai
Hong Tang
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2022
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-022-07466-4

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