Teaching fiberoptic-assisted tracheoscopy in very low birth weight infants: A randomized controlled simulator study

Author:

Wolf Monika,Seiler Berenike,Vogelsang Valentina,Sydney Hopf Luke,Moll-Koshrawi Parisa,Vettorazzi Eik,Ebenebe Chinedu Ulrich,Singer Dominique,Deindl Philipp

Abstract

ObjectiveWe developed a fiberoptic-assisted tracheoscopy (FAST) method to avoid direct laryngoscopy during surfactant replacement therapy and compared two training approaches on a very low birth weight (VLBW) infant simulator.DesignThis prospective randomized controlled study was conducted at the Department of Neonatology and Pediatric Intensive Care Medicine of the University Medical Center Hamburg-Eppendorf, Germany.ParticipantsWe recruited physicians, trainees, students, and nurses without prior experience in endoscopic techniques.InterventionsParticipants were assigned randomly to a group that received instructions according to Peyton’s Four-Step Approach and a control group that received standard bedside teaching only.Main outcome measuresPrimary endpoints were the total and the component times required to place the bronchoscope and the method success.ResultsWe recruited 186 participants. Compared with the control group, the Peyton group had a lower mean (±standard deviation) FAST completion time (33.2 ± 27.5 s vs. 79.5 ± 47.9 s, p < 0.001; d = 1.12) and a higher FAST success rate (95% vs. 84%, p = 0.036, V = 0.18).ConclusionAfter standardized training, the vast majority of novices completed FAST successfully. Peyton’s four-step approach resulted in faster and more successful performance than standardized training.

Publisher

Frontiers Media SA

Subject

Pediatrics, Perinatology and Child Health

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