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A Novel Triage Tool of Artificial Intelligence Assisted Diagnosis Aid System for Suspected COVID-19 Pneumonia in Fever Clinics

68 Pages Posted: 19 Mar 2020

See all articles by Cong Feng

Cong Feng

Government of the People's Republic of China - Department of Emergency

Zhi Huang

Purdue University - School of Electrical and Computer Engineering

Lili Wang

Government of the People's Republic of China - Chinese PLA General Hospital

Xin Chen

Government of the People's Republic of China - Fever clinic

Yongzhi Zhai

Government of the People's Republic of China - Fever clinic

Feng Zhu

Government of the People's Republic of China - Fever clinic

Hua Chen

Government of the People's Republic of China - Fever clinic

Yingchan Wang

Government of the People's Republic of China - Fever clinic

Xiangzheng Su

Government of the People's Republic of China - Fever clinic

Sai Huang

Government of the People's Republic of China - Department of Hematology

Lin Tian

Government of the People's Republic of China - Fever clinic

Weixiu Zhu

Government of the People's Republic of China - Fever clinic

Wenzheng Sun

Government of the People's Republic of China - Fever clinic

Liping Zhang

Government of the People's Republic of China - Fever clinic

Qingru Han

Government of the People's Republic of China - Fever clinic

Juan Zhang

Government of the People's Republic of China - Fever clinic

Fei Pan

Government of the People's Republic of China - Fever clinic

Li Chen

Government of the People's Republic of China - Fever clinic

Zhihong Zhu

Government of the People's Republic of China - Fever clinic

Hongju Xiao

Government of the People's Republic of China - Fever clinic

Yu Liu

Government of the People's Republic of China - Fever clinic

Gang Liu

Government of the People's Republic of China - Fever clinic

Wei Chen

Government of the People's Republic of China - Fever clinic

Tanshi Li

Government of the People's Republic of China - Fever clinic

More...

Abstract

Background: Currently, the prevention and control of COVID-19 outside Hubei province in China, and other countries has become more and more critically serious. We developed and validated a diagnosis aid model without CT images for early identification of suspected COVID-19 pneumonia (S-COVID-19-P) on admission in adult fever patients and made the validated model available via an online triage calculator.

Methods: Patients admitted from Jan 14 to Feb 26, 2020 with the epidemiological history of exposure to COVID-19 were included [Model development (n = 132) and validation (n = 32)]. Candidate features included clinical symptoms, routine laboratory tests and other clinical information on admission. Features selection and model development were based on Lasso regression. The primary outcome is the development and validation of a diagnosis aid model for S-COVID-19-P early identification on admission.

Findings: The development cohort contains 26 S-COVID-19-P and 7 confirmed COVID-19 pneumonia cases. The final selected features included 1 variables of demographic information, 4 variables of vital signs, 5 variables of blood routine values, 7 variables of clinical signs and symptoms, 1 infection-related biomarker. The model performance in held-out testing set and validation cohort resulted in AUCs of 0.841 and 0.938, F-1 score of 0.571 and 0.667, recall of 1.000 and 1.000, specificity of 0.727 and 0.778, and the precision of 0.400 and 0.500. The top 5 important features were Age, IL-6, SYS_BP, MONO%, and Fever classification. Based on this model, an optimized strategy for S-COVID-19-P early identification in fever clinics has also been designed.

Interpretation: S-COVID-19-P could be identified early by a machine-learning model only used collected clinical information without CT images on admission in fever clinics with 100% recall score. The well performed and validated model has been deployed as an online triage tool, which is available at: https://intensivecare.shinyapps.io/COVID19/ .

Funding Statement: The present study was supported by grants from the PLA Science and Technology Project (14CXZ005, AWS15J004, 16BJZ19), National Key R&D Program of China (2019YFF0302300), Construction Project of Key Disciplines in the 13th Five-Year Plan of the PLA (Traumatic Surgery in the Battlefield, 2019-126, 2019-513), Beijing Science and Technology New Star Project (XX2018019/Z181100006218028), the PLA General Hospital Science and technology Project (2019XXJSYX20, 2018XXFC-20, ZH19016).

Declaration of Interests: The authors declare that they have no conflict of interest.

Ethics Approval Statement: Data collection was passive and had no impact on patient safety. This study was approved by the PLA General Hospital ethics committee.

Keywords: Suspected COVID-19 pneumonia; Diagnosis Aid model; Fever Clinics; Machine Learning

Suggested Citation

Feng, Cong and Huang, Zhi and Wang, Lili and Chen, Xin and Zhai, Yongzhi and Zhu, Feng and Chen, Hua and Wang, Yingchan and Su, Xiangzheng and Huang, Sai and Tian, Lin and Zhu, Weixiu and Sun, Wenzheng and Zhang, Liping and Han, Qingru and Zhang, Juan and Pan, Fei and Chen, Li and Zhu, Zhihong and Xiao, Hongju and Liu, Yu and Liu, Gang and Chen, Wei and Li, Tanshi, A Novel Triage Tool of Artificial Intelligence Assisted Diagnosis Aid System for Suspected COVID-19 Pneumonia in Fever Clinics (3/8/2020). Available at SSRN: https://ssrn.com/abstract=3551355 or http://dx.doi.org/10.2139/ssrn.3551355

Cong Feng (Contact Author)

Government of the People's Republic of China - Department of Emergency ( email )

Beijing
China

Zhi Huang

Purdue University - School of Electrical and Computer Engineering

West Lafayette, IN
United States

Lili Wang

Government of the People's Republic of China - Chinese PLA General Hospital

Beijing, 100853
China

Xin Chen

Government of the People's Republic of China - Fever clinic

Beijing
China

Yongzhi Zhai

Government of the People's Republic of China - Fever clinic

Beijing
China

Feng Zhu

Government of the People's Republic of China - Fever clinic

Beijing
China

Hua Chen

Government of the People's Republic of China - Fever clinic

Beijing
China

Yingchan Wang

Government of the People's Republic of China - Fever clinic

Beijing
China

Xiangzheng Su

Government of the People's Republic of China - Fever clinic

Beijing
China

Sai Huang

Government of the People's Republic of China - Department of Hematology

Beijing
China

Lin Tian

Government of the People's Republic of China - Fever clinic

Beijing
China

Weixiu Zhu

Government of the People's Republic of China - Fever clinic

Beijing
China

Wenzheng Sun

Government of the People's Republic of China - Fever clinic

Beijing
China

Liping Zhang

Government of the People's Republic of China - Fever clinic

Beijing
China

Qingru Han

Government of the People's Republic of China - Fever clinic

Beijing
China

Juan Zhang

Government of the People's Republic of China - Fever clinic

Beijing
China

Fei Pan

Government of the People's Republic of China - Fever clinic

Beijing
China

Li Chen

Government of the People's Republic of China - Fever clinic

Beijing
China

Zhihong Zhu

Government of the People's Republic of China - Fever clinic

Beijing
China

Hongju Xiao

Government of the People's Republic of China - Fever clinic

Beijing
China

Yu Liu

Government of the People's Republic of China - Fever clinic

Beijing
China

Gang Liu

Government of the People's Republic of China - Fever clinic

Beijing
China

Wei Chen

Government of the People's Republic of China - Fever clinic ( email )

Beijing
China

Tanshi Li

Government of the People's Republic of China - Fever clinic ( email )

Beijing
China

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