Assessment of Learning Curve for Radiofrequency Ablation in Twin Reversed Arterial Perfusion Sequence: A Simulation Model Study

Author:

Chaiperm Tanchanok1,Phithakwatchara Nisarat1ORCID,Nawapun Katika1,Viboonchart Sommai1,Jaingam Suparat1,Watananirun Kanokwaroon1,Wataganara Tuangsit1ORCID

Affiliation:

1. Division of Maternal‐Fetal Medicine Faculty of Medicine Siriraj Hospital Department of Obstetrics and Gynecology Mahidol University Bangkok Thailand

Abstract

ABSTRACTObjectiveThis study characterized the procedural learning curve of novice practitioners in mastering radiofrequency ablation (RFA) in a simulated twin reversed arterial perfusion sequence (TRAPS) model.MethodTwelve novices practiced RFA in a TRAPS model, which was evaluated for validity. A learning curve CUSUM analysis was performed to define the number of procedures required to achieve competency. The learning plateau of needle insertion time and the number of procedures required to surpass 90% of the learning plateau were calculated.ResultsThe overall model rating of 4.26 ± 0.58 serves as validating the high learning performance. A success rate of 92.8% was achieved across 767 procedures. The average number of procedures required to achieve technical competency was 29 relative to years of experience in minimally invasive prenatal testing. After reaching this competency level, the success rate improved from 88.2% to 96.7% (P < 0.001). The needle insertion time learning curve indicated that 90% of the learning plateau was reached after 21 procedures, with the learning plateau occurring at 27.5s.ConclusionPerformance in RFA within the simulated TRAPS model improved over time. Achieving competency enhanced technical success and shortened the needle insertion process. This simulation training provides practical skills for inexperienced surgeons.Trial RegistrationTCTR20221005001

Funder

Faculty of Medicine Siriraj Hospital, Mahidol University

Publisher

Wiley

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1.7亿篇,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 © 2019-2025 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