ArticleFrontiers in cardiovascular medicine2024
Construction and validation of coronary heart disease risk prediction model for general hospitals in Tacheng Prefecture, Xinjiang, China.
Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Utility of artificial intelligence in predicting clinical outcomes of angiographic procedures: a comprehensive scoping review.Journal of cardiovascular imaging · 2026Review
- Machine learning and SHAP values for predicting coronary artery disease risk in Xinjiang, China.European journal of medical research · 2026Article
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9 authors.
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Abstract
Objective: 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. Results: 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 Conclusion: 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.
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