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Development and external validation of a COVID-19 mortality risk prediction algorithm: a multicentre retrospective cohort study.
Mei, Jin; Hu, Weihua; Chen, Qijian; Li, Chang; Chen, Zaishu; Fan, Yanjie; Tian, Shuwei; Zhang, Zhuheng; Li, Bin; Ye, Qifa; Yue, Jiang; Wang, Qiao-Li.
  • Mei J; Central Laboratory, Ningbo First Hospital, Zhejiang University, Ningbo, China.
  • Hu W; Department of Respiratory and Critical Care, Jingzhou First People's Hospital, Jingzhou, China.
  • Chen Q; Emergency Department, Fifth Hospital in Wuhan, Wuhan, Hubei, China.
  • Li C; Department of Cardiology, Hubei No.3 People's Hospital of Jianghan University, Wuhan, Hubei, China.
  • Chen Z; Department of Cardiology, Internal Medicine, Jiayu People's Hospital, Jiayu, China.
  • Fan Y; Department of Pharmacology, School of Basic Medical Sciences, Wuhan University, Wuhan, China.
  • Tian S; Department of Pharmacology, School of Basic Medical Sciences, Wuhan University, Wuhan, China.
  • Zhang Z; Department of Pharmacology, School of Basic Medical Sciences, Wuhan University, Wuhan, China.
  • Li B; Department of Pharmacology, School of Basic Medical Sciences, Wuhan University, Wuhan, China.
  • Ye Q; Institute of Hepatobiliary Diseases of Wuhan University, Zhongnan Hospital of Wuhan University, Wuhan, China.
  • Yue J; Department of Pharmacology, School of Basic Medical Sciences, Wuhan University, Wuhan, China yuejiang@whu.edu.cn qiaoli.wang@ki.se.
  • Wang QL; Hubei Province Key Laboratory of Allergy and Immunology, Wuhan, China.
BMJ Open ; 10(12): e044028, 2020 12 24.
Article in English | MEDLINE | ID: covidwho-999261
ABSTRACT

OBJECTIVE:

This study aimed to develop and externally validate a COVID-19 mortality risk prediction algorithm.

DESIGN:

Retrospective cohort study.

SETTING:

Five designated tertiary hospitals for COVID-19 in Hubei province, China.

PARTICIPANTS:

We routinely collected medical data of 1364 confirmed adult patients with COVID-19 between 8 January and 19 March 2020. Among them, 1088 patients from two designated hospitals in Wuhan were used to develop the prognostic model, and 276 patients from three hospitals outside Wuhan were used for external validation. All patients were followed up for a maximal of 60 days after the diagnosis of COVID-19.

METHODS:

The model discrimination was assessed by the area under the receiver operating characteristic curve (AUC) and Somers' D test, and calibration was examined by the calibration plot. Decision curve analysis was conducted. MAIN OUTCOME

MEASURES:

The primary outcome was all-cause mortality within 60 days after the diagnosis of COVID-19.

RESULTS:

The full model included seven predictors of age, respiratory failure, white cell count, lymphocytes, platelets, D-dimer and lactate dehydrogenase. The simple model contained five indicators of age, respiratory failure, coronary heart disease, renal failure and heart failure. After cross-validation, the AUC statistics based on derivation cohort were 0.96 (95% CI, 0.96 to 0.97) for the full model and 0.92 (95% CI, 0.89 to 0.95) for the simple model. The AUC statistics based on the external validation cohort were 0.97 (95% CI, 0.96 to 0.98) for the full model and 0.88 (95% CI, 0.80 to 0.96) for the simple model. Good calibration accuracy of these two models was found in the derivation and validation cohort.

CONCLUSION:

The prediction models showed good model performance in identifying patients with COVID-19 with a high risk of death in 60 days. It may be useful for acute risk classification. WEB CALCULATOR We provided a freely accessible web calculator (https//www.whuyijia.com/).
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Risk Assessment / Pandemics / SARS-CoV-2 / COVID-19 / Hospitalization Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Asia Language: English Journal: BMJ Open Year: 2020 Document Type: Article Affiliation country: Bmjopen-2020-044028

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Risk Assessment / Pandemics / SARS-CoV-2 / COVID-19 / Hospitalization Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Asia Language: English Journal: BMJ Open Year: 2020 Document Type: Article Affiliation country: Bmjopen-2020-044028