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ORIGINAL RESEARCH article

Front. Cardiovasc. Med.
Sec. Clinical and Translational Cardiovascular Medicine
Volume 11 - 2024 | doi: 10.3389/fcvm.2024.1514103
This article is part of the Research Topic Novel Translational Advances in Artificial Intelligence for Diagnosis and Treatment of Cardiovascular Diseases View all 6 articles

Construction and validation of coronary heart disease risk prediction model for general hospitals in Tacheng Prefecture, Xinjiang, China

Provisionally accepted
Yikang Xu Yikang Xu 1Jingru Ma Jingru Ma 1Yang Yang Yang Yang 1LImin Liu LImin Liu 1Xinran Zhao Xinran Zhao 1Yu Wang Yu Wang 2*Alimu Mijiti Alimu Mijiti 3Qianru Cheng Qianru Cheng 3Jun Ma Jun Ma 3
  • 1 Second Affiliated Hospital of Shenyang Medical College, Shenyang, Liaoning Province, China
  • 2 Shenyang Medical College, Shenyang, Liaoning Province, China
  • 3 Tacheng People's Hospital, Tacheng, China, Tacheng, China

The final, formatted version of the article will be published soon.

    To analyze the risk factors for coronary heart disease (CHD) in patients hospitalized in general hospitals in the Tacheng Prefecture, Xinjiang, and to construct and verify the nomogram prediction model for the risk of CHD.Methods: From June 2022 to June 2023, 489 CHD patients (CHD group) and 520 non-CHD individuals (control group) in Tacheng, Xinjiang, were retrospectively selected. Using a 7:3 ratio, patients were divided into a training group (706 cases) and a validation group (303 cases). General clinical data were compared, and key variables were screened using logistic regression (AIC). A CHD risk nomogram for Tacheng was constructed. Model performance was assessed using ROC AUC, calibration curves, and DCA.In the training group, non-Han Chinese (OR=2.93, 95%CI 2.0-4.3), male (OR=1.65, 95%CI 1.0-2.7), alcohol consumption (OR=1.82, 95%CI 1.2-2.9), hyperlipidemia (OR=2.41, 95%CI 1.7-3.5), smoking (OR=1.61, 95%CI 1.0-2.6), diabetes mellitus (OR=1.62, 95%CI 1.1-2.4), stroke (OR=2.39, 95%CI 1.6-3.7), older age (OR=1.08, 95%CI 1.1-1.2), and larger waist circumference (OR=1.04, 95%CI 1.0-1.1) were the risk factors for coronary heart disease (all P<0.05). The area under the curve (AUC) of the work characteristics of the subjects in the training group and the validation group were 0.80 (95%CI 0.8-0.8) and 0.82 (95%CI 0.8-0.9), respectively.The Hosmer-Lemeshow test indicated P=0.325 for the training group and P=0.130 for the validation group, with calibration curves closely fitting the ideal curve. The predicted values aligned well with actual values, and decision curve analysis results suggest that the model offers a net clinical benefit.The CHD risk prediction model developed in this study for general hospitals in Tacheng Prefecture, Xinjiang, demonstrates strong predictive performance and serves as a simple, user-friendly, cost-effective tool for medical personnel to identify high-risk groups for CHD.

    Keywords: Tacheng Prefecture, Xinjiang, coronary heart disease, Nomograms, risk prediction, Logistic regression

    Received: 20 Oct 2024; Accepted: 22 Nov 2024.

    Copyright: © 2024 Xu, Ma, Yang, Liu, Zhao, Wang, Mijiti, Cheng and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yu Wang, Shenyang Medical College, Shenyang, 110034, Liaoning Province, China

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