Evidence map›Paper›PMID 40016247›Full record

ArticleScientific reports2025

Construction of a prediction model for coronary heart disease in type 2 diabetes mellitus: a cross-sectional study.

Huiling Zhang, Hui Shi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Huiling ZhangLaboratory of Geriatric Nursing and Health, School of Nursing, Anhui Univerity of Traditional Chinese Medicine, No.103 Meishan Road, Hefei, 230012, Anhui Province, China. 1101090886@qq.com.
Hui ShiLaboratory of Geriatric Nursing and Health, School of Nursing, Anhui Univerity of Traditional Chinese Medicine, No.103 Meishan Road, Hefei, 230012, Anhui Province, China. ymf149@126.com.

Funding

Anhui Provincial Higher Education Quality Engineering Project: 2023jyxm0354This work was supported by Anhui Provincial Higher Education Institution Key Project of Natural Science Research No.2023AH050774
6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM), as a globally prevalent metabolic disorder, is continuously rising in prevalence and significantly increases the risk of developing coronary heart disease (CHD). Studies have shown that the risk of CHD is higher in T2DM patients compared to those without diabetes, making early identification and prevention essential. Therefore, establishing an effective prediction model to identify high-risk individuals for CHD among T2DM patients is crucial. This study aims to develop and validate a prediction model for coronary heart disease in patients with type 2 diabetes mellitus, accurately identifying high-risk individuals to support early intervention and personalized treatment. The study included 423 patients with type 2 diabetes mellitus (T2DM) who were hospitalized in the endocrinology department of a tertiary hospital in Anhui Province between February 1, 2023, and February 1, 2024. Based on the presence of hypertension, patients were divided into a T2DM with coronary heart disease (CHD) group (193 patients) and a T2DM group (230 patients). Data were collected through questionnaires and clinical indicators. Univariate and multivariate logistic regression analyses were used to identify significant predictors, and the model was validated. Model performance was evaluated using the ROC curve and AUC value. Hypertension, smoking, neuropathy, vascular complications, cerebral infarction, bilateral lower extremity arteriosclerosis, microalbuminuria, and elevated uric acid levels. were identified as significant predictors for T2DM with hypertension. The AUC of the prediction model was 0.83, indicating good predictive performance. The prediction model developed in this study effectively identifies high-risk patients with T2DM and CHD, providing a reliable tool for clinical use. This model facilitates early intervention and personalized treatment for hypertension, smoking, neuropathy, vascular complications, cerebral infarction, bilateral lower extremity arteriosclerosis, microalbuminuria, and elevated uric acid levels, improving overall health outcomes for patient.

Indexed as

Coronary DiseaseDiabetes Mellitus, Type 2AgedChinaCross-Sectional StudiesFemaleHumansHypertensionMaleMiddle AgedRisk FactorsROC Curve

Identifiers

PMID40016247
PMCPMC11868600

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.