Establishment of a scoring model based on ultrasonic characteristics for predicting the restenosis after superficial femoral artery stenting
10.3760/cma.j.cn131148-20200726-00603
- VernacularTitle:基于超声征象建立股浅动脉支架再狭窄的风险预测评分模型
- Author:
Mingjie GAO
;
Yang HUA
;
Lingyun JIA
;
Xinyu ZHAO
;
Ran LIU
;
Bing TIAN
;
Xinyuan CHU
- From:
Chinese Journal of Ultrasonography
2021;30(1):42-47
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a comprehensive and effective scoring model based on ultrasonic characteristics for predicting the restenosis risk after superficial femoral artery stenting, in order to assess the possibility of in-stent restenosis and to provide guidance for the selection of therapeutic strategies.Methods:A retrospective review of a database of 328 patients (381 limbs) undergoing superficial femoral artery stents in Xuanwu Hospital, Capital Medical University from January 2016 to January 2018 was made as a modeling group.In the modeling cohort, the multivariate logistic regression analysis was performed to screen independent risk factors for in-stent restenosis. A predictive scoring model of restenosis risk was established with weighted score of independent risk factors according to the odd ratio values. Based on the best cut-off value of the receiver operating characteristic (ROC) curves, the scoring table was divided into low-risk and high-risk groups of restenosis.Results:Multivariate logistic regression analysis showed that 8 factors were included in the score system to establish the scoring model of in-stent restenosis risk prediction including calcified plaque, peak systolic velocity of popliteal artery<40 cm/s, runoff scores≥4, ankle-brachial index<0.5, female (1 point each); complicated stroke, complicated chronic renal disease, total lesion length 15.0-24.9 cm (2 points each); total lesion length≥25.0 cm (3 points), a total of 12 points in the model. The validation indicated that the scoring system had good predictive value(AUC=0.775, 95% CI=0.727-0.824, P<0.001) and goodness of fit (Hosmer-Lemeshow χ 2=4.921, P=0.766). The agreement with digital subtraction angiography(DSA) was good (Kappa value=0.609). The scoring system was further divided into the low-risk restenosis (0-5 points) and high-risk restenosis (6-12 points) according to the best cut-off value of 5.5, with a sensitivity of 68.1%, a specificity of 74.6%, and the accuracy of 72.7%. Conclusions:The superficial femoral artery in-stent restenosis risk predicting score model based on ultrasonic characteristics may accurately predict the restenosis preoperatively. It provides a theoretical basis for the precise surgical plans.
