Wang Yiwei, Gao Mingjie, Zhao Xinyu, Han Peng, Zhang Libo, Dardik Alan
Department of Ultrasound in Medicine, Beijing Luhe Hospital, Capital Medical University, Beijing, China.
Department of Ultrasound in Medicine, Beijing Luhe Hospital, Capital Medical University, Beijing, China.
Ann Vasc Surg. 2025 Apr;113:175-185. doi: 10.1016/j.avsg.2024.12.068. Epub 2025 Jan 23.
Prediction of in-stent restenosis (ISR) is clinically important for patients with peripheral artery disease (PAD) in superficial femoral artery (SFA) who have been treated with stenting. The aim of this study was to construct and validate a predictive model for ISR after SFA stenting based on a series of clinical and ultrasonic parameters.
This retrospective study included 381 patients who were treated with self-expanding bare nitinol stents in their SFA at our hospital between January 1, 2018, and January 1, 2022. These patients were randomly allocated to a training cohort (266 patients) or a validation cohort (115). Clinical and ultrasonic parameters related to ISR (>50%) in the SFA at 12 months were derived by univariable and multivariable logistic regression analyses to create a nomogram model predictive of risk of ISR. Receiver operating characteristic (ROC) curve analyses were used to assess the recognition ability of the model. A calibration curve was used to evaluate the model's calibration ability, and decision curve analysis was used to validate the nomogram's clinical utility.
Logistic regression analyses showed that sex, echogenicity of the target plaque, preoperative arterial runoff score, preoperative popliteal artery flow rate, lesion length, and residual diameter were risk factors for ISR; these parameters were used to construct the nomogram model. Internal and external validation showed that the areas under the ROC curves were 0.82 (95% CI: 0.77-0.87) and 0.70 (95% CI: 0.60-0.79), respectively, suggesting good recognition ability of the model. Additionally, calibration curves for the predictive model indicated good calibration, and the decision curve analysis demonstrated clinical utility of the model.
This novel nomogram that predicts ISR after SFA stenting demonstrated excellent discriminatory power, calibration capacity, and clinical usefulness.
对于接受支架置入治疗的股浅动脉（SFA）外周动脉疾病（PAD）患者，预测支架内再狭窄（ISR）具有重要的临床意义。本研究旨在基于一系列临床和超声参数构建并验证SFA支架置入术后ISR的预测模型。
本回顾性研究纳入了2018年1月1日至2022年1月1日期间在我院接受SFA自膨式裸镍钛合金支架治疗的381例患者。这些患者被随机分为训练队列（266例患者）或验证队列（115例）。通过单变量和多变量逻辑回归分析得出与12个月时SFA中ISR（>50%）相关的临床和超声参数，以创建预测ISR风险的列线图模型。采用受试者操作特征（ROC）曲线分析评估模型的识别能力。使用校准曲线评估模型的校准能力，并使用决策曲线分析验证列线图的临床实用性。
逻辑回归分析显示，性别、目标斑块的回声性、术前动脉血流评分、术前腘动脉血流速度、病变长度和残余直径是ISR的危险因素；这些参数用于构建列线图模型。内部和外部验证显示，ROC曲线下面积分别为0.82（95%CI：0.77-0.87）和0.70（95%CI：0.60-0.79），表明模型具有良好的识别能力。此外，预测模型的校准曲线显示校准良好，决策曲线分析证明了模型的临床实用性。
这种预测SFA支架置入术后ISR的新型列线图具有出色的区分能力、校准能力和临床实用性。
