Establishment and Validation of a Risk Prediction Model for Non-complete Procedural Success in Patients Undergoing Transvenous Lead Extraction
10.3969/j.issn.1000-3614.2025.08.012
- VernacularTitle:心血管植入型电子器械经静脉导线拔除非完全成功风险预测模型的构建与验证
- Author:
Xinxin ZHANG
1
;
Feng ZE
;
Xuebin LI
;
Haicheng ZHANG
;
Jiangbo DUAN
;
Dandan YANG
;
Ding LI
;
Long WANG
;
Jinshan HE
Author Information
1. 北京大学人民医院 心内科,北京 100044;邯郸市中心医院 心内科,邯郸 056001
- Publication Type:Journal Article
- Keywords:
transvenous lead extraction;
risk factor;
abandoned lead;
prediction model
- From:
Chinese Circulation Journal
2025;40(8):806-812
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.
