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2型糖尿病冠心病预测模型的构建:一项横断面研究

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

作者信息

Zhang Huiling, Shi Hui

机构信息

Laboratory of Geriatric Nursing and Health, School of Nursing, Anhui Univerity of Traditional Chinese Medicine, No.103 Meishan Road, Hefei, 230012, Anhui Province, China.

出版信息

Sci Rep. 2025 Feb 27;15(1):7003. doi: 10.1038/s41598-025-85692-x.

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.

摘要

2型糖尿病(T2DM)作为一种全球流行的代谢性疾病,其患病率持续上升,并显著增加了患冠心病(CHD)的风险。研究表明,与非糖尿病患者相比,T2DM患者患CHD的风险更高,因此早期识别和预防至关重要。因此,建立一个有效的预测模型以识别T2DM患者中CHD的高危个体至关重要。本研究旨在开发并验证2型糖尿病患者冠心病的预测模型,准确识别高危个体以支持早期干预和个性化治疗。该研究纳入了2023年2月1日至2024年2月1日期间在安徽省一家三级医院内分泌科住院的423例2型糖尿病(T2DM)患者。根据是否存在高血压,将患者分为2型糖尿病合并冠心病(CHD)组(193例患者)和2型糖尿病组(230例患者)。通过问卷调查和临床指标收集数据。采用单因素和多因素逻辑回归分析来识别显著预测因素,并对模型进行验证。使用ROC曲线和AUC值评估模型性能。高血压、吸烟、神经病变、血管并发症、脑梗死、双侧下肢动脉硬化、微量白蛋白尿和尿酸水平升高被确定为T2DM合并高血压的显著预测因素。预测模型的AUC为0.83,表明具有良好的预测性能。本研究开发的预测模型有效地识别了T2DM和CHD的高危患者,为临床应用提供了可靠的工具。该模型有助于对高血压、吸烟、神经病变、血管并发症、脑梗死、双侧下肢动脉硬化、微量白蛋白尿和尿酸水平升高进行早期干预和个性化治疗,改善患者的整体健康结局。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/553f/11868600/353996e0f8fb/41598_2025_85692_Fig1_HTML.jpg

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