新疆塔城地区冠心病患者冠脉多支病变发病风险列线图预测模型的构建
R541.4; 目的 分析新疆塔城地区冠心病患者冠脉多支病变的危险因素,并构建冠脉多支病变发病风险的列线图预测模型.方法 通过查阅患者电子病历,回顾性收集并分析2021年1月至2023年6月期间在塔城市人民医院心内科住院治疗的348例冠心病患者的临床资料,所有患者均接受选择性冠脉造影术,其中单支病变167例,多支病变181例.使用随机数表法将348例患者按7∶3的比例分为训练组(n=243)和验证组(n=105),训练组数据用于模型构建,验证组数据用于模型验证.比较两组患者的临床资料,基于赤池信息准则(AIC),单因素和多因素Logistic双向逐步回归法筛选出关键模型变量,构建塔城地区冠脉多...
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| Published in | 海南医学 Vol. 35; no. 19; pp. 2743 - 2748 |
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| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
沈阳医学院附属第二医院心内科,辽宁 沈阳 110001%辽宁中医药大学护理学院,辽宁 沈阳 110033%塔城市人民医院心内科,新疆 塔城 834700
2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1003-6350 |
| DOI | 10.3969/j.issn.1003-6350.2024.19.002 |
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| Abstract | R541.4; 目的 分析新疆塔城地区冠心病患者冠脉多支病变的危险因素,并构建冠脉多支病变发病风险的列线图预测模型.方法 通过查阅患者电子病历,回顾性收集并分析2021年1月至2023年6月期间在塔城市人民医院心内科住院治疗的348例冠心病患者的临床资料,所有患者均接受选择性冠脉造影术,其中单支病变167例,多支病变181例.使用随机数表法将348例患者按7∶3的比例分为训练组(n=243)和验证组(n=105),训练组数据用于模型构建,验证组数据用于模型验证.比较两组患者的临床资料,基于赤池信息准则(AIC),单因素和多因素Logistic双向逐步回归法筛选出关键模型变量,构建塔城地区冠脉多支病变发病风险的列线图预测模型.利用受试者工作特征(ROC)曲线下面积(AUC)、校准曲线和临床决策曲线(DCA)综合评估模型的区分度、校准度和临床实用性.结果 训练组中,经单因素和多因素Logistic双向逐步回归法分析结果显示,年龄、吸烟、陈旧心肌梗死是冠脉多支病变的危险因素(P＜0.05),而无糖尿病是冠脉多支病变的保护因素(P＜0.05);基于上述关键因子构建并绘制MVD风险列线图预测模型;ROC曲线分析结果显示,训练组和验证组的AUC分别为0.720(95%CI:0.656～0.783)和0.707(95%CI:0.586～0.789),两组校准曲线与理想曲线拟合度均良好,预测值与实际值相契合,两组临床决策曲线结果均提示本模型具备临床净获益.结论 本研究构建的新疆塔城地区冠心病患者冠脉多支病变发病风险预测模型预测性能良好,可为本地区快速识别冠脉多支病变高风险人群提供高效工具. |
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| AbstractList | R541.4; 目的 分析新疆塔城地区冠心病患者冠脉多支病变的危险因素,并构建冠脉多支病变发病风险的列线图预测模型.方法 通过查阅患者电子病历,回顾性收集并分析2021年1月至2023年6月期间在塔城市人民医院心内科住院治疗的348例冠心病患者的临床资料,所有患者均接受选择性冠脉造影术,其中单支病变167例,多支病变181例.使用随机数表法将348例患者按7∶3的比例分为训练组(n=243)和验证组(n=105),训练组数据用于模型构建,验证组数据用于模型验证.比较两组患者的临床资料,基于赤池信息准则(AIC),单因素和多因素Logistic双向逐步回归法筛选出关键模型变量,构建塔城地区冠脉多支病变发病风险的列线图预测模型.利用受试者工作特征(ROC)曲线下面积(AUC)、校准曲线和临床决策曲线(DCA)综合评估模型的区分度、校准度和临床实用性.结果 训练组中,经单因素和多因素Logistic双向逐步回归法分析结果显示,年龄、吸烟、陈旧心肌梗死是冠脉多支病变的危险因素(P＜0.05),而无糖尿病是冠脉多支病变的保护因素(P＜0.05);基于上述关键因子构建并绘制MVD风险列线图预测模型;ROC曲线分析结果显示,训练组和验证组的AUC分别为0.720(95%CI:0.656～0.783)和0.707(95%CI:0.586～0.789),两组校准曲线与理想曲线拟合度均良好,预测值与实际值相契合,两组临床决策曲线结果均提示本模型具备临床净获益.结论 本研究构建的新疆塔城地区冠心病患者冠脉多支病变发病风险预测模型预测性能良好,可为本地区快速识别冠脉多支病变高风险人群提供高效工具. |
| Abstract_FL | Objective To analyze the risk factors of coronary multivessel disease in patients with coronary heart disease in Tacheng Prefecture,Xinjiang,and construct the nomogram prediction model for the risk of coronary mul-tivessel disease.Methods The clinical data of 348 patients with coronary heart disease hospitalized in the Department of Cardiology,Tacheng People's Hospital between January 2021 and June 2023 were retrospectively collected and ana-lyzed by reviewing the patients'electronic medical records.All the patients included in the study underwent selective cor-onary angiography,and they were classified into single vessel disease(n=167)and multivessel disease(n=181)accord-ing to the results of the coronary angiography.The patients were also divided into training group(n=243)and validation group(n=105)in the ratio of 7∶3.The data of the training group were used for model construction,and the data of the validation group were used for model validation.The clinical data of patients in the two groups were compared,and based on the Akaike Information Criteria(AIC),the key model variables were screened out by single-factor and multi-ple-factor logistic regression to construct the nomogram prediction model for the risk of coronary multivessel disease in Tacheng area.The discrimination,calibration,and clinical practicality of the mode were comprehensively evaluated us-ing the area under the receiver operating characteristic(ROC)curve(AUC),calibration curve,and clinical decision curve analysis(DCA).Results In the training group,age,smoking,and old myocardial infarction were risk factors for coronary multivessel disease(P＜0.05),and non-diabetes was a protective factor for coronary multivessel disease(P＜0.05).ROC curve showed that the AUC in the training group and validation group were 0.720(95%CI:0.656-0.783)and 0.707(95%CI:0.586-0.789),respectively.The calibration curves of both groups were well fitted to the ideal curve,and the pre-dicted values were consistent with the actual values.The clinical DCA of both groups indicated that this model had clini-cal net benefits.Conclusion The risk prediction model for coronary multivessel disease in the Tacheng area of Xinji-ang constructed in this study has good predictive performance and can provide efficient tools for quickly identifying high-risk populations with coronary multivessel disease in the local area. |
| Author | 徐以康 占凯雯 孙斯琪 张志峰 刘蕾 马军 李曼曼 杨洋 马晶茹 |
| AuthorAffiliation | 沈阳医学院附属第二医院心内科,辽宁 沈阳 110001%辽宁中医药大学护理学院,辽宁 沈阳 110033%塔城市人民医院心内科,新疆 塔城 834700 |
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| Author_FL | LIU Lei YANG Yang ZHANG Kai-wen LI Man-man XU Yi-kang MA Jing-ru SUN Si-qi ZHANG Zhi-feng MA Jun |
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| DocumentTitle_FL | Construction of the nomogram prediction model for the risk of coronary multivessel disease in patients with coronary heart disease in Tacheng area,Xinjiang |
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| Keywords | 冠脉多支病变 Coronary multivessel disease 列线图 Nomograms Tacheng area,Xinjiang Risk prediction 冠心病 Coronary heart disease 新疆塔城地区 风险预测 |
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| Snippet | R541.4; 目的 分析新疆塔城地区冠心病患者冠脉多支病变的危险因素,并构建冠脉多支病变发病风险的列线图预测模型.方法... |
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| Title | 新疆塔城地区冠心病患者冠脉多支病变发病风险列线图预测模型的构建 |
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