【摘要】 目的 本研究旨在分析卵圆孔未闭(PFO)患者的解剖学结构及超声心动图特征，探讨PFO患者发生隐源性脑卒中(CS)的独立影响因素，联合构建多参数模型，以提高预测效能。方法 回顾性分析山西省人民医院2023年1月—2024年12月收治的PFO患者的临床资料、血清学指标及超声参数，根据是否合并CS分为CS组(51例)和非CS组(69例)。采用单因素及多因素logistic回归分析PFO患者发生CS的独立影响因素，联合构建多参数模型，应用ROC曲线评估多参数模型的预测效能。结果 单因素logistic回归分析显示PFO内径、隧道长度、Valsalva动作下右向左分流分级、合并房间隔膨出瘤、D-二聚体(DD)、中性粒细胞/淋巴细胞比值(NLR)、空腹血糖及甘油三酯-葡萄糖(TyG)指数在两组间差异具有统计学意义(P<0.05);多因素logistic回归分析显示：PFO内径、DD、NLR及TyG指数是PFO患者发生CS的独立影响因素。联合构建多参数模型的AUC为0.775,提示该模型具有良好的预测效能。结论 经食管超声心动图联合经胸超声心动图右心声学造影、DD、NLR及TyG指数构建的多参数模型，提高了对PFO患者发生CS的预测效能。更多还原

【Abstract】 Objective This study aims to analyze the anatomical structure and echocardiographic features of patients with patent foramen ovale(PFO),explore the independent influencing factors for the occurrence of cryptogenic stroke(CS) in PFO patients, and jointly construct a multi-parameter model to improve the predictive efficacy.Methods A retrospective analysis was conducted on the clinical data, serological indicators, and ultrasound parameters of patients with PFO admitted to Shanxi Provincial People’s Hospital from January 2023 to December 2024.The patients were divided into the CS group(51 cases) and the non-CS group(69 cases) based on whether they developed CS.Univariate and multivariate logistic regression analyses were used to identify the independent influencing factors for the occurrence of CS in PFO patients.A multi-parameter model was jointly constructed, and the predictive efficacy of the multi-parameter model was evaluated using the ROC curve.Results The single-factor logistic regression analysis showed that the diameters of the PFO,the length of the tunnel, the grading of right-to-left shunt during the Valsalva maneuver, the presence of atrial septal aneurysm, D-dimer(DD),the neutrophil/lymphocyte ratio(NLR),fasting blood glucose, and the triglyceride-glucose(TyG) index showed statistically significant differences between the two groups(P<0.05);the multivariate logistic regression analysis revealed that the diameters of the PFO,DD,NLR,and TyG index were independent influencing factors for the occurrence of CS in PFO patients.The AUC of the multi-parameter model constructed in combination was 0.775,suggesting that this model has good predictive efficacy.Conclusion The multi-parameter model constructed by combining transesophageal echocardiography with DD,NLR and TyG indices has significantly improved the predictive efficacy for the occurrence of combined CS in patients with PFO.更多还原