Predictors and clinical outcomes of permanent pacemaker implantation after transcatheter aortic valve implantation

Author:

Chen Bing-Ying,Huang Ting-Feng,Jiang Xin-Da,Ding Xiao-Yan,Zhou Xiao-Fen

Abstract

Abstract Objective This study aimed to identify the incidence, risk factors, and outcomes of permanent pacemaker (PPM) implantation after transcatheter aortic valve implantation (TAVI) procedures. Methods A retrospective analysis was conducted on 70 patients who underwent TAVI at the Department of Cardiology, Fujian Provincial Hospital, from January 2018 to March 2022. Based on whether a new PPM was implanted after TAVI, all patients were divided into two groups: NEW PPM and NO PPM. Baseline characteristics and clinical data were compared between the two groups. Univariate analysis was used to analyze different variables between the two groups. A binary logistic regression analysis was used to evaluate independent correlates for PPM implantation after TAVI. Results The mean age of the 70 patients was 73.1 ± 8.8 years. The incidence of PPM implantation was 17.1%. Patients with diabetes and chronic kidney disease were more likely to require PPM (50% vs. 20.7%, p = 0.042, 25% vs. 5.2%, p = 0.042). Our study did not identify any significant differences in the incidence of electrocardiographic conduction disturbances except for the previous right bundle branch block (RBBB) (NO PPM 6.9% vs. NEW PPM 33.3%, p < 0.05). We found that prosthesis size, implantation depth, procedural duration, and length of hospital and intensive care unit (ICU) stays were comparable between the two groups. The leading independent predictors of PPM implantation were previous RBBB (odds ratio 10.129, p = 0.034). Conclusion The previous RBBB was the leading independent predictor of PPM implantation. New PPM was not associated with significantly new-onset left BBB, extended post-procedure hospitalization, ICU stay, or procedural duration. Graphical Abstract

Funder

the General Program of Natural Science Foundation of Fujian Province

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3