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ENGLISH ABSTRACT
2型糖尿病患者发生心脑血管并发症的影响因素分析及风险预测模型构建
芮珉
王剑杰
凌志刚
作者及单位信息
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DOI： 10.3760/cma.j.cn114015-20240613-00439
Analysis of influencing factors and construction of risk prediction model for cardio-cerebrovascular complications in patients with type 2 diabetes mellitus
Rui Min
Wang Jianjie
Ling Zhigang
Authors Info & Affiliations
Rui Min
Department of Pharmacy, Huangshan City People′s Hospital, Anhui Province, Huangshan 245000, China
Wang Jianjie
Department of Pharmacy, Huangshan City People′s Hospital, Anhui Province, Huangshan 245000, China
Ling Zhigang
Department of Pharmacy, Huangshan City People′s Hospital, Anhui Province, Huangshan 245000, China
·
DOI： 10.3760/cma.j.cn114015-20240613-00439
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摘要

目的了解2型糖尿病（T2DM）患者发生心脑血管并发症的影响因素，构建列线图风险预测模型。

方法研究设计为前瞻性临床观察研究，研究对象选自黄山市人民医院2022年5月—2023年4月收治的T2DM住院患者。应用医院电子病历系统收集患者性别、年龄、体重指数、饮酒、吸烟情况、家族性疾病史、胰岛素使用情况、T2DM病程、血压及实验室检查结果。出院时进行T2DM患者特异性用药信念量表（总分10~50分）、药物素养评估量表（总分0~7分）、Morisky服药依从性量表（总分0~8分）测评；出院后电话随访6个月。以是否发生心脑血管并发症将患者分为2组。应用SPSS 26.0软件进行logistic回归分析，筛选T2DM患者出现心脑血管并发症的影响因素；应用R 4.1.0软件构建列线图预测模型，以Bootstrap法对列线图模型进行内部验证。

结果共294例T2DM患者纳入分析，用药信念评分为（32.6±5.6）分，药物素养评分为（4.2±0.5）分，服药依从性评分为（6.1±0.8）分。随访6个月，共有43例（14.6%）发生心脑血管并发症，包括冠心病（23例）、心力衰竭（12例）、脑卒中（8例）。与无心脑血管并发症组相比，心脑血管并发症组患者体重指数、糖化血红蛋白（HbA1c）、D-二聚体、血尿酸较高，用药信念评分、药物素养评分、服药依从性评分较低（均 P<0.05）。二元logistic回归分析结果显示，HbA1c、D-二聚体、血尿酸、用药信念、药物素养、服药依从性是T2DM患者发生心脑血管并发症的影响因素。依此建立列线图预测模型，内部验证结果显示，一致性指数为0.958，受试者工作特征曲线下面积为0.824，校准曲线趋近于理想曲线。

结论T2DM患者用药信念、药物素养和服药依从性现状并不理想。HbA1c、D-二聚体和血尿酸水平高，用药信念、药物素养和服药依从性差是T2DM患者发生心脑血管并发症的危险因素，综合多种因素建立列线图模型，对预测该类风险具有较高价值。

糖尿病，2型;心血管疾病;脑血管障碍;药物素养;用药信念;服药依从性;心脑血管并发症;风险预测模型
ABSTRACT

ObjectiveTo understand the influencing factors for cardio-cerebrovascular complications in patients with T2DM and construct a nomogram risk prediction.

MethodsThe study design was a prospective observational study, and the subjects were selected from hospitalized patients with T2DM admitted to Huangshan City People′s Hospital from May 2022 to April 2023. Data on patients' gender, age, body mass index, alcohol consumption, smoking status, family history of cardio-cerebrovascular diseases, insulin use, duration of diabetes, blood pressure, and routine laboratory test results were collected using the hospital electronic medical record system. At discharge, patients were assessed using the T2DM-Specific Medication Belief Scale (total score range: 10-50), Medication Literacy Assessment Scale (total score range: 0-7), and Morisky Medication Adherence Scale (total score range: 0-8). Patients were followed up by telephone for 6 months after discharge and divided into 2 groups based on the occurrence of cardio-cerebrovascular complications. Logistic regression analysis was performed using SPSS 26.0 software to identify influencing factors for cardio-cerebrovascular complications in T2DM patients. A nomogram prediction model was constructed using R 4.1.0 software, and internal validation of the model was conducted using the Bootstrap method.

ResultsA total of 294 T2DM patients were included in the analysis. The medication belief score was (32.6±5.6) score, the medication literacy score was (4.2±0.5) score, and the medication adherence score was (6.1±0.8) score. During the 6-month follow-up, a total of 43 patients (14.6%) experienced cardio-cerebrovascular complications, including of coronary heart disease (23 cases), heart failure (12 cases), and stroke (8 cases). Compared to patients without cardio-cerebrovascular complications, patients with complications had higher body mass index, glycosylated hemoglobin A1c (HbA1c), D-dimer, and uric acid levels, as well as lower medication belief scores, medication literacy scores, and medication adherence scores (all P<0.05). Binary logistic regression analysis showed that HbA1c, D-dimer, uric acid, medication belief, medication literacy, and medication adherence were influencing factors for cardio-cerebrovascular complications in T2DM patients. Accordingly, a nomogram prediction model was established. Internal validation results of the model showed that the concordance index was 0.958, the area under the receiver operating characteristic curve was 0.824, and the calibration curve was close to the ideal curve.

ConclusionsThe current status of medication belief, medication literacy, and medication adherence in T2DM patients was not ideal. High levels of HbA1c, D-dimer, and uric acid, as well as poor medication belief, medication literacy, and medication adherence were risk factors for cardio-cerebrovascular complications in T2DM patients. The nomogram model, which integrated multiple influencing factors, had high value in predicting the risks.

Diabetes mellitus, type 2;Cardiovascular diseases;Cerebrovascular disorders;Medication literacy;Beliefs about medications;Medication adherence;Cardio-cerebrovascular complications;Risk prediction model
Rui Min, Email: mocdef.3ab6121709891nimgnib
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引用本文

芮珉,王剑杰,凌志刚. 2型糖尿病患者发生心脑血管并发症的影响因素分析及风险预测模型构建[J]. 药物不良反应杂志,2025,27(03)：162-168.

DOI:10.3760/cma.j.cn114015-20240613-00439

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糖尿病是一种代谢性疾病，以慢性高血糖为主要标志，其中2型糖尿病（type 2 diabetic mellitus，T2DM）占比高达90% [ 1 ]。2021年，全球共有5.37亿糖尿病患者，而我国糖尿病患者数约有1.4亿人，位居世界首位 [ 2 ]。当前，糖尿病仍无法治愈，临床主要通过药物、运动、饮食控制等手段进行血糖控制，控制不佳会大大增加相关心脑血管并发症发生风险。其中，冠心病和心力衰竭为T2DM常见并发症，是导致T2DM患者致残致死的主要原因 [ 3 , 4 ]。
良好的服药依从性有助于改善T2DM患者血糖水平，减缓疾病进展，减少心脑血管并发症。然而，服药依从性良好的T2DM患者占比低于25% [ 5 , 6 , 7 ]。有研究者认为，患者对疾病的认知和用药信念是影响其行为导向的重要因素，由此产生的不同情绪反应和应对行为，直接或间接地造成临床结局不同 [ 8 ]。积极的用药信念可促进患者持续用药治疗 [ 9 ]。糖尿病患者用药信念是指其对降糖药物的看法、观点或判断 [ 10 ]。认为降糖药物不必要使用、担心降糖药物不良反应的患者，用药依从性普遍较差，导致血糖控制不良，进一步增加急诊就诊率、住院率和病死率。药物素养是指个体在获取、理解、处理药物信息的基础上做出决策的能力。患者药物素养较差可导致药物不良事件和并发症发生风险增高 [ 11 ]。疾病预后往往受患者治疗行为的影响，治疗行为的改变一般基于且后发于患者对疾病认知或治疗信念的改变。本研究分析T2DM患者心脑血管并发症影响因素，探索其与用药信念、药物素养和服药依从性的相关性；构建风险预测模型，以期为减少T2DM患者心脑血管并发症提供依据。
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芮珉，Email： mocdef.3ab6121709891nimgnib
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芮珉：数据整理与分析、论文撰写与修改；王剑杰、凌志刚：研究设计、数据整理与分析

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