A gender specific risk assessment of coronary heart disease based on physical examination data.

Autor: Yang H; School of Computer Science, Chengdu University of Information Technology, Chengdu, 610225, China.; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Luo YM; School of Medical Information and Engineering, Southwest Medical University, Luzhou, 646000, China.; Medical Engineering & Medical Informatics Integration and Transformational Medicine Key Laboratory of Luzhou City, Luzhou, 646000, China., Ma CY; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Zhang TY; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Zhou T; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Ren XL; Sichuan Chuanjiang Science and Technology Research Institute Co., Ltd, Luzhou, 646000, China., He XL; Sichuan Chuanjiang Science and Technology Research Institute Co., Ltd, Luzhou, 646000, China., Deng KJ; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Yan D; Beijing Institute of Clinical Pharmacy, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China., Tang H; School of Basic Medical Sciences, Southwest Medical University, Luzhou, 646000, China. huatang@swmu.edu.cn.; Central Nervous System Drug Key Laboratory of Sichuan Province, Luzhou, 646000, China. huatang@swmu.edu.cn., Lin H; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 610054, China. hlin@uestc.edu.cn.
Jazyk: angličtina
Zdroj: NPJ digital medicine [NPJ Digit Med] 2023 Jul 31; Vol. 6 (1), pp. 136. Date of Electronic Publication: 2023 Jul 31.
DOI: 10.1038/s41746-023-00887-8
Abstrakt: Large-scale screening for the risk of coronary heart disease (CHD) is crucial for its prevention and management. Physical examination data has the advantages of wide coverage, large capacity, and easy collection. Therefore, here we report a gender-specific cascading system for risk assessment of CHD based on physical examination data. The dataset consists of 39,538 CHD patients and 640,465 healthy individuals from the Luzhou Health Commission in Sichuan, China. Fifty physical examination characteristics were considered, and after feature screening, ten risk factors were identified. To facilitate large-scale CHD risk screening, a CHD risk model was developed using a fully connected network (FCN). For males, the model achieves AUCs of 0.8671 and 0.8659, respectively on the independent test set and the external validation set. For females, the AUCs of the model are 0.8991 and 0.9006, respectively on the independent test set and the external validation set. Furthermore, to enhance the convenience and flexibility of the model in clinical and real-life scenarios, we established a CHD risk scorecard base on logistic regression (LR). The results show that, for both males and females, the AUCs of the scorecard on the independent test set and the external verification set are only slightly lower (<0.05) than those of the corresponding prediction model, indicating that the scorecard construction does not result in a significant loss of information. To promote CHD personal lifestyle management, an online CHD risk assessment system has been established, which can be freely accessed at http://lin-group.cn/server/CHD/index.html .
(© 2023. The Author(s).)
Databáze: MEDLINE
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