心肌桥患者合并冠状动脉痉挛风险预测列线图模型构建研究

Establishment of Nomogram Model for Risk Prediction of Myocardial Bridge Patients Combined with Coronary Artery Spasm

背景心肌桥(MB)是一种先天性的冠状动脉发育异常,可引起一系列心血管症状,目前国内尚缺乏针对MB患者合并冠状动脉痉挛(CAS)风险的有效预测手段。目的筛选MB患者合并CAS的危险因素并构建其风险预测列线图模型。方法选取2018年10月至2020年10月因胸痛入住阜阳市人民医院并经冠状动脉造影(CAG)确诊为MB的住院患者183例作为研究对象,根据其是否合并CAS分为MB-CAS组(n=94)和单纯MB组(n=89)。比较两组患者临床资料,MB患者合并CAS的影响因素分析采用多因素Logistic回归分析。采用R语言(R 3.5.3)软件包和rms程序包绘制MB患者合并CAS风险预测列线图模型;采用Bootstrap法重复抽样1000次进行模型验证,计算一致性指数(CI)并绘制校正曲线、受试者工作特征(ROC)曲线、决策曲线以评估该列线图模型的预测效能。结果两组患者年龄、吸烟情况、饮酒情况、高血压发生率、MB分级比较,差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,年龄、吸烟情况、饮酒情况、高血压及MB分级是MB患者合并CAS的独立影响因素(P<0.05)。基于年龄、吸烟情况、饮酒情况、高血压及MB分级构建MB患者合并CAS风险预测列线图模型。模型验证结果显示,CI为0.712;该列线图模型预测MB患者合并CAS风险的校正曲线趋近于理想曲线,提示该列线图模型具有良好的预测精度;ROC曲线分析结果显示,列线图模型预测MB患者合并CAS风险的ROC曲线下面积为0.761〔95%CI(0.732,0.801)〕,提示该列线图模型具有良好的区分度;决策曲线分析结果显示,在10%~89%范围内该列线图模型预测MB患者合并CAS风险的净获益值较高,提示该列线图模型临床预测效能良好。结论基于年龄、吸烟情况、饮酒情况、高血压及MB分级构建的MB患者合并CAS风险预测列线图模型有助于临床工作者及早识别伴有CAS高风险的MB患者,具有一定临床价值。

Background Myocardial bridge(MB)is a common congenital dysplasia that can cause a series of cardiovascular symptoms.At present,there is no effective predicting method for the risk of MB patients combined with coronary artery spasm(MB-CAS)in China.Objective To screen the risk factors of MB patients combined with CAS and construct its risk prediction nomogram model.Methods A total of 183 inpatients admitted to Fu Yang People's Hospital due to chest pain and diagnosed with MB by coronary angiography(CAG)from October 2018 to October 2020 were selected as the research objects.They were divided into MB-CAS group(n=94)and simple MB group(n=89)according to whether combined with CAS or not.The clinical data were compared between the two groups.The influencing factors of MB patients combined with CAS were analyzed by multivariate Logistic regression analysis.The nomogram model of risk prediction of MB patients combined with CAS was constructed by R language(R 3.5.3)software package and rms program package;the Bootstrap method was used to repeatedly sample 1000 times for model verification,the consistency index(CI)was calculated and the calibration curve,receiver operating characteristic(ROC)curve,decision curve were drawn to evaluate the prediction efficiency of the nomogram model.Results There were significant differences in age,smoking,drinking,incidence of hypertension and MB grade between the two groups(P<0.05).Multivariate Logistic regression analysis showed that age,smoking,drinking,hypertension and MB grade were independent influencing factors of MB patients combined with CAS(P<0.05).A nomogram model for predicting the risk of MB patients combined with CAS was constructed based on age,smoking,drinking,hypertension and MB grade.The model validation results showed that the CI was 0.712;the calibration curve of the nomogram model for predicting the risk of MB patients combined with CAS was close to the ideal curve,indicating that the nomogram model had good prediction accuracy;the ROC curve analysis results showed that the area under the ROC curve of the nomogram model for predicting the risk of MB patients combined with CAS was 0.761[95%CI(0.732,0.801)],indicating that the nomogram model had good discrimination;the decision curve analysis results showed that,in the range of 10%-89%,the net benefit of the nomogram model for predicting the risk of MB patients combined with CAS was higher,indicating that the nomogram model had good clinical prediction efficiency.Conclusion The nomogram model for predicting the risk of MB patients combined with CAS based on age,smoking,drinking,hypertension and MB grade is helpful for clinical workers to identify MB patients combined with high risk of CAS as soon as possible,and has certain clinical value.