Establishment of a risk prediction model of patent foramen ovale detected by transoesophageal echocardiography
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,which can be utilized as a new assessment tool for medical staff to assess the risk of PFO that favors the formulation of individualized nursing decisions.
万方数据
维普
