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Predicting progression to severe COVID-19 using the PAINT score
Ming Wang1,2, Dongbo Wu1,2, Chang-Hai Liu1
1Center of Infectious Diseases, West China Hospital, Sichuan University, 37 Guoxue Lane, Chengdu, Sichuan Province, 610041, People's Republic of China.
Insights
A new predictive score, the PAINT score, helps identify patients with COVID-19 at high risk of severe disease progression. This tool aids clinicians in early intervention for coronavirus disease 2019 patients.
Area of Science:
- Infectious Diseases
- Clinical Medicine
- Biostatistics
Background:
- Predicting the severity of coronavirus disease 2019 (COVID-19) is crucial for effective patient management.
- Early identification of patients likely to progress from mild/moderate to severe disease is a significant clinical challenge.
Purpose of the Study:
- To develop and validate a novel predictive score for identifying COVID-19 patients at high risk of disease progression.
- To establish a reliable tool for clinical decision-making in managing COVID-19.
Main Methods:
- Retrospective analysis of 239 hospitalized COVID-19 patients from two Chinese medical centers.
- Utilized Cox proportional hazards model and Kaplan-Meier methods to identify independent predictors of disease progression.
- Developed the PAINT score based on five key prognostic factors: pulmonary disease, age > 75, IgM, CD16+/CD56+ NK cells, and aspartate aminotransferase.
Main Results:
- A total of 23 patients (9.62%) progressed to severe COVID-19.
- The PAINT score demonstrated high predictive accuracy with a C-index of 0.91.
- Validation through nomogram, bootstrap analysis, calibration curves, and decision curves confirmed the score's robust predictive value.
Conclusions:
- The PAINT score is a valuable tool for predicting progression from mild/moderate to severe COVID-19.
- This score can assist clinicians in identifying high-risk individuals, enabling timely and targeted interventions.
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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