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初治冠心病患者在医院-家庭过渡期的用药偏差预测模型构建与验证
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| 篇名： | 初治冠心病患者在医院-家庭过渡期的用药偏差预测模型构建与验证 |
| TITLE： | Construction and validation of a medication deviation prediction model for hospital-to-home transition period in coronary heart disease patients with initial treatment |
| 摘要： | 目的 开发初治冠心病患者医院-家庭过渡期用药偏差风险预测模型，以助力医务人员快速识别用药偏差高危人群。方法纳入2024年1－7月华北理工大学附属医院（以下简称“我院”）的462例初治住院冠心病患者。将患者随机分为建模组与内部验证组。建模组患者依据是否发生用药偏差，分为用药偏差组和非用药偏差组。同法收集2025年6－9月我院心血管内科的57例初治住院冠心病患者作为外部验证组。采用单因素分析筛选预测因子，进一步通过多因素Logistic回归分析构建预测模型，并采用内部验证方法评估模型性能，采用外部验证方法检验模型的泛化能力。结果462例患者被分为建模组（319例）和内部验证组（143例）。在建模组中，用药偏差组有192例（占比60.19%），非用药偏差组有127例（占比39.81%）。多因素Logistic回归分析结果显示，年龄、药品种类、服药依从性、合理服药自我效能是初治冠心病患者用药偏差发生的预测因子（P＜0.05），预测模型方程为logitP＝ln[P（/1－P）]＝1.321+1.732×年龄+4.091×药品种类－4.360×服药依从性－3.081×合理服药自我效能。模型区分度良好，Hosmer-Lemeshow检验拟合的P值为0.439，受试者工作特征曲线下面积（AUC）为0.870，灵敏度为0.970，特异度为0.607；绘制了总分为350分、截断值为110分的风险列线图；内部验证组患者的AUC为0.787，预测准确率为77.6%；外部验证组患者的AUC为0.802，预测准确率为73.7%。结论本研究成功构建了初治冠心病患者医院-家庭过渡期用药偏差风险预测模型，此模型具备良好的区分度与预测准确率，识别出高龄（＞70岁）、药品种类≥5种、服药依从性差、合理服药自我效能差为用药偏差的独立危险因素。 |
| ABSTRACT： | OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations. |
| 期刊： | 2026年第37卷第04期 |
| 作者： | 李玉双；李殊；张倩影；黄炎；刘坤；谷秀林；蒋欢欢 |
| AUTHORS： | LI Yushuang，LI Shu，ZHANG Qianying，HUANG Yan，LIU Kun，GU Xiulin，JIANG Huanhuan |
| 关键字： | 冠心病；用药偏差；医院-家庭过渡期；影响因素；预测模型 |
| KEYWORDS： | coronary heart disease； medication deviation； hospital-to-home transition period； influencing factors； predictive model |
| 阅读数： | 3 次 |
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