METHODS: The patient cohort was divided into two groups based on the presence or absence of PMV post-surgery. Comprehensive preoperative and intraoperative clinical data were collected. Univariate and multivariate logistic regression analyses were employed to identify risk factors contributing to the incidence of PMV. Based on the logistic regression results, a clinical nomogram was developed.
RESULTS: The study included 550 patients who underwent valve surgery, among whom 62 (11.27%) developed PMV. Multivariate logistic regression analysis revealed that age (odds ratio [OR] = 1.082, 95% confidence interval [CI] = 1.042-1.125; P < 0.000), current smokers (OR = 1.953, 95% CI = 1.007-3.787; P = 0.047), left atrial internal diameter index (OR = 1.04, 95% CI = 1.002-1.081; P = 0.041), red blood cell count (OR = 0.49, 95% CI = 0.275-0.876; P = 0.016), and aortic clamping time (OR = 1.031, 95% CI = 1.005-1.057; P < 0.017) independently influenced the occurrence of PMV. A nomogram was constructed based on these factors. In addition, a receiver operating characteristic (ROC) curve was plotted, with an area under the curve (AUC) of 0.782 and an accuracy of 0.884.
CONCLUSIONS: Age, current smokers, left atrial diameter index, red blood cell count, and aortic clamping time are independent risk factors for PMV in patients undergoing valve surgery. Furthermore, the nomogram based on these factors demonstrates the potential for predicting the risk of PMV in patients following valve surgery.
方法:根据手术后是否存在PMV,将患者队列分为两组。收集术前和术中综合临床资料。采用单变量和多变量逻辑回归分析来确定导致PMV发生率的危险因素。根据逻辑回归结果,绘制了临床列线图。
结果:该研究包括550名接受瓣膜手术的患者,其中62人(11.27%)发生PMV。多因素logistic回归分析显示年龄(比值比[OR]=1.082,95%置信区间[CI]=1.042-1.125;P<0.000),当前吸烟者(OR=1.953,95%CI=1.007-3.787;P=0.047),左心房内径指数(OR=1.04,95%CI=1.002-1.081;P=0.041),红细胞计数(OR=0.49,95%CI=0.275-0.876;P=0.016),主动脉阻断时间(OR=1.031,95%CI=1.005~1.057,P<0.017)独立影响PMV的发生。基于这些因素构建了列线图。此外,绘制了受试者工作特性(ROC)曲线,曲线下面积(AUC)为0.782,准确度为0.884。
结论:年龄,当前吸烟者,左心房直径指数,红细胞计数,主动脉阻断时间是瓣膜手术患者PMV的独立危险因素。此外,基于这些因素的列线图显示了预测瓣膜手术后患者PMV风险的潜力.