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Progression of severity in coronavirus disease 2019 patients before treatment and a self-assessment scale to predict disease severity.
Yao, Ye; Tian, Jie; Meng, Xia; Kan, Haidong; Zhou, Lian; Wang, Weibing.
  • Yao Y; Department of Biostatics, School of Public Health, Fudan University, Shanghai, 200032, China.
  • Tian J; School of Public Health & Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China.
  • Meng X; Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China.
  • Kan H; Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China. kanh@fudan.edu.cn.
  • Zhou L; Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, 200032, China. kanh@fudan.edu.cn.
  • Wang W; Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Gulou District, Nanjing, 210009, China. jonneylian@163.com.
BMC Infect Dis ; 22(1): 409, 2022 Apr 26.
Article in English | MEDLINE | ID: covidwho-1817191
ABSTRACT

OBJECTIVES:

This study aims to further investigate the association of COVID-19 disease severity with numerous patient characteristics, and to develop a convenient severity prediction scale for use in self-assessment at home or in preliminary screening in community healthcare settings. SETTING AND

PARTICIPANTS:

Data from 45,450 patients infected with COVID-19 from January 1 to February 27, 2020 were extracted from the municipal Notifiable Disease Report System in Wuhan, China. PRIMARY AND SECONDARY OUTCOME

MEASURES:

We categorized COVID-19 disease severity, based on The Chinese Diagnosis and Treatment Protocol for COVID-19, as "nonsevere" (which grouped asymptomatic, mild, and ordinary disease) versus "severe" (grouping severe and critical illness).

RESULTS:

Twelve scale items-age, gender, illness duration, dyspnea, shortness of breath (clinical evidence of altered breathing), hypertension, pulmonary disease, diabetes, cardio/cerebrovascular disease, number of comorbidities, neutrophil percentage, and lymphocyte percentage-were identified and showed good predictive ability (area under the curve = 0·72). After excluding the community healthcare laboratory parameters, the remaining model (the final self-assessment scale) showed similar area under the curve (= 0·71).

CONCLUSIONS:

Our COVID-19 severity self-assessment scale can be used by patients in the community to predict their risk of developing severe illness and the need for further medical assistance. The tool is also practical for use in preliminary screening in community healthcare settings. Our study constructed a COVID-19 severity self-assessment scale that can be used by patients in the community to predict their risk of developing severe illness and the need for further medical assistance.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Self-Assessment / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: S12879-022-07386-3

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Self-Assessment / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: S12879-022-07386-3