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The PAINTS Score for Predicting Severe COVID-19: A Multi-Center Study in Zhejiang, China

21 Pages Posted: 10 Aug 2021

See all articles by Ting Li

Ting Li

Wenzhou Medical University

Ye Gao

Wenzhou Medical University

Fang Gao-Smith

affiliation not provided to SSRN

Chenchen Jiang

Military Hospital Begin - Clinical Research Unit

Chanfan Zheng

Wenzhou Medical University

Jingwei Zheng

Dazhou Central Hospital - Department of Clinical Research Center

Zhongwang Li

Wenzhou Medical University - Department of Intensive Care Unit

Jiansheng Zhu

Wenzhou Medical University - Department of Infectious Diseases

Shengwei Jin

Wenzhou Medical University - Department of Anesthesia and Critical Care

Xiaokun Li

Wenzhou Medical University - Institute of Virology

More...

Abstract

Background: To develop and validate a risk-scoring model for predicting severe COVID-19 at presentation.

Methods: Entire patients with COVID-19 in three cities in Zhejiang, China from December 2019 to February 2020 were analyzed retrospectively. The risk-scoring model was developed with nomogram using multivariate logistic regression and externally validated by the patients from two other cities near Wenzhou.  

Findings: Severe COVID-19 was detected 58 out of 488 (11·9%) eligible patients in the primary cohort and 24 out of 153 (15·7%) in the validation cohort. The sex (OR 4·11, 95% CI 1·38 to 14·05), body mass index >25 kg/m2 (OR 6·14, 95% CI 2·05 to 21·29), hypertension (OR 4·97, 95% CI 1·73 to 15·37), neutrophil/lymphocyte ratio (3-6) (OR 8·04, 95% CI 2·51 to 29·52), albumin (35-40) g/L (OR 37·96, 95% CI 5·49 to 825·34) and platelets >300×109/L (OR 6·76, 95% CI 1·55 to 32·47) were independent predictors of severe COVID-19. The risk-scoring model-PAINTS performed excellent discrimination with AUC 0·98, 95% CI 0·96 to 1·00 in the primary cohort and AUC 0·78 (95% CI, 0·67 to 0·89) in the validation cohort. Interpretation: PAINTS score may guide clinical decision-making efficiently and allocate limited medical resources reasonably.  

Funding: The National Key New Drug Creation and Manufacturing Program, Ministry of Science and Technology (CN) [2020ZX09201002]; Wenzhou Science and Technology Key Problem Program [ZY2020001]; The Primary Research and Development Plan of Zhejiang Province [2019C03011] and the Natural Science Foundation of Zhejiang Province [LQ20H150002].

Declaration of Interest: None to declare.

Ethical Approval: The study was conducted under the amended Declaration of Helsinki and approved by the Institutional Review Board (IRB) of Wenzhou Medical University (No.2020-002). The written consent was waived by the Institutional Review Board (IRB) of Wenzhou Medical University (No.2020-002)

Suggested Citation

Li, Ting and Gao, Ye and Gao-Smith, Fang and Jiang, Chenchen and Zheng, Chanfan and Zheng, Jingwei and Li, Zhongwang and Zhu, Jiansheng and Jin, Shengwei and Li, Xiaokun, The PAINTS Score for Predicting Severe COVID-19: A Multi-Center Study in Zhejiang, China. Available at SSRN: https://ssrn.com/abstract=3902471 or http://dx.doi.org/10.2139/ssrn.3902471

Ting Li

Wenzhou Medical University

Zhejiang Province
China

Ye Gao

Wenzhou Medical University

Zhejiang Province
China

Fang Gao-Smith

affiliation not provided to SSRN

No Address Available

Chenchen Jiang

Military Hospital Begin - Clinical Research Unit

France

Chanfan Zheng

Wenzhou Medical University ( email )

Zhejiang Province
China

Jingwei Zheng

Dazhou Central Hospital - Department of Clinical Research Center

No.56 Nanyuemiao Street
Dazhou, 635000
China

Zhongwang Li

Wenzhou Medical University - Department of Intensive Care Unit

China

Jiansheng Zhu

Wenzhou Medical University - Department of Infectious Diseases ( email )

150 Ximen Road of Linhai City
Taizhou
China

Shengwei Jin (Contact Author)

Wenzhou Medical University - Department of Anesthesia and Critical Care ( email )

Wenzhou
China

Xiaokun Li

Wenzhou Medical University - Institute of Virology ( email )

Zhejiang, Wenzhou
China