摘要
目的分析致病性卵圆孔未闭(PFO)的危险因素并构建风险评估模型,为制订临床护理方案提供依据。方法回顾性分析2022年7月至2023年7月徐州医科大学附属连云港医院收治的110例PFO患者临床资料,根据是否发生隐匿性脑血管意外(CVA)分为CVA组42例和非CVA组68例。收集患者临床资料及经食管超声心动图评估参数,采用单因素和多因素Logistic回归分析PFO患者发生CVA的危险因素并建立风险预测模型,通过绘制ROC曲线评价模型的预测效能。结果CVA组和非CVA组在高血压病、高脂血症、房间隔膨出瘤、房间隔高移动性发生率以及甘油三酯、半胱氨酸、PFO高度、PFO隧道长度等指标的差异有统计学意义(P<0.05)。以是否发生CVA作为因变量,将单因素分析中有统计学意义的指标作为自变量进行多因素Logistic回归分析,结果显示,高脂血症、PFO高度、房间隔膨出瘤、房间隔高移动性是PFO患者发生CVA的独立危险因素(P<0.05)。根据多因素分析结果,建立CVA风险预测模型为:Logit(P)=-2.613+1.442×高脂血症+2.610×PFO高度+1.194×房间隔膨出瘤+1.309×房间隔高移动性,模型中变量的意义分别为:高脂血症(0=无,1=是),PFO高度为实际测量值,房间隔膨出瘤(0=无,1=是),房间隔高移动性(0=无,1=是)。Hosmer-Lemeshow检验的P>0.05,说明预测模型的预测值与实际值差异无统计学意义,模型拟合优度较好。以CVA预测概率作为检验变量进行ROC分析,结果显示该预测模型的曲线下面积为0.866(95%CI:0.787~0.923,P<0.01),最佳临界值为0.635,特异性为77.9%,敏感性为81.0%,约登指数为0.589。结论基于危险因素建立的风险预测模型能预测PFO发生CVA风险,可成为医护人员评估有PFO致病风险的工具,有利于护理人员制订个体化的护理决策。
Objective To analyze the risk factors of patent foramen ovale(PFO)and to construct a prediction model,so as to provide a basis for formulating clinical nursing plans.Methods Clinical data of 110 PFO patients admitted to Affiliated Lianyungang Hospital of Xuzhou Medical University from July 2022 to July 2023 were retrospectively analyzed.According to the occurrence of cryptogenic cerebrovascular accident(CVA),patients were assigned into the CVA group(42 cases)and non-CVA group(68 cases).The clinical data and parameters of transesophageal echocardiography were collected.Univariate and multivariate logistic regression analyses were performed to identify the risk factors of CVA in PFO patients.A CVA risk prediction model was created,and its predictive efficacy was evaluated by plotting the receiver operating characteristic(ROC)curves.Results There were significant differences in the incidence of hypertension,hyperlipidemia,atrial septal bulge,atrial septal hypermobility,triglycerides,cysteine,patent foramen ovale(PFO),and PFO tunnel length between the CVA group and the non-CVA group(P<0.05).Multivariate logistic regression analysis was performed with CVA as the dependent variable and significant indicators in the univariate analysis as independent variables.The results showed that hyperlipidemia,PFO height,atrial septal bulge,and atrial septal hypermobility were independent risk factors for CVA in PFO patients(P<0.05).Hosmer-Lemeshow test of P>0.05 indicated that the difference between the predicted value and the actual value of the prediction model was not statistically significant.The goodness of fit of the model was good.Receiver operating characteristic(ROC)analysis of the CVA prediction probability showed that the area under the curve(AUC)of the prediction model was 0.866(95%CI:0.787-0.923,P<0.01),with the optimal cut-off of 0.635,specificity of 77.9%,sensitivity of 81.0%and Youden index of 0.589.Conclusion The CVA risk prediction model in PFO patients can effectively predict the risk of CVA in PFO patients,whic
作者
马亚利
徐艳
赵蓓
王慧
陈允安
范乐乐
MA Yali;XU Yan;ZHAO Bei(Department of Neurology,Affiliated Lianyungang Hospital of Xuzhou Medical University,Jiangsu,Lian yungang 222000,China;不详)
出处
《河北医药》
CAS
2024年第19期3018-3021,共4页
Hebei Medical Journal
基金
连云港市卫生科技项目(编号:202004)。
关键词
卵圆孔未闭
不明原因脑血管意外
经食管超声心动图
patent foramen ovale
cryptogenic cerebrovascular accident
transoesophageal echocardiography
