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确定机器人子宫切除术的能力指标:一项系统综述

Determining the metrics of competence in robotic hysterectomy: a systematic review.

作者信息

Arcamo Kayla, Murugappan Sita, Larkins Kirsten, Mohan Helen, Costello Anthony, Pendlebury Adam, McNally Orla, McBain Rosie

机构信息

International Medical Robotics Academy, Parkville, Melbourne, Australia.

University of Melbourne, Parkville, Melbourne, Australia.

出版信息

J Robot Surg. 2025 Jun 13;19(1):286. doi: 10.1007/s11701-025-02471-6.

Abstract

With the rapidly increasing use of robotic-assisted surgery in gynecology, there is a clear need for a structured robotic hysterectomy curriculum. To develop an effective training program, valid performance metrics that reliably assess skill level is required. As part of robotic curriculum development with IMRA using Kern's framework, this systematic review aims to identify proposed metrics of competence and assess their validity within the context of robotic hysterectomy training. A systematic literature search of OVID MEDLINE and EMBASE was conducted following the PRISMA guidelines, with keywords related to 'hysterectomy', 'robot-assisted', and 'metric'. The study aims, methods, outcomes, description of metrics, measurements of metrics, and metrics validity were extracted and analyzed. The initial search yielded 531 articles, of which 3 were included. Three additional articles were identified through citation and website searching, resulting in a total of six articles being included in this review. Development and identification of both simulator and intraoperative metrics greatly varied between the studies. Several studies utilized an expert consensus-based methodology, such as a modified Delphi methodology, to develop performance metrics. All metrics were assessed for content, construct, and predictive validity. Two studies were able to demonstrate predictive validity; however, there was limited correlation between virtual reality simulator metrics and intraoperative scores. This review highlights the lack of standardized and validated metrics specific to robotic hysterectomy, as well as the inability of established assessment tools to differentiate between robotic surgical skill level. This forms the context for ongoing work at IMRA to develop a granular assessment tool to assess skill acquisition as part of a robotic hysterectomy curriculum.

摘要

随着机器人辅助手术在妇科领域的使用迅速增加,显然需要一个结构化的机器人子宫切除术课程。为了制定一个有效的培训计划,需要有可靠评估技能水平的有效性能指标。作为使用克恩框架与IMRA合作开展机器人课程开发的一部分,本系统评价旨在确定所提议的能力指标,并在机器人子宫切除术培训的背景下评估其有效性。按照PRISMA指南,对OVID MEDLINE和EMBASE进行了系统的文献检索,关键词涉及“子宫切除术”“机器人辅助”和“指标”。提取并分析了研究目的、方法、结果、指标描述、指标测量以及指标有效性。初步检索得到531篇文章,其中3篇被纳入。通过引文和网站搜索又确定了3篇文章,最终共有6篇文章被纳入本评价。不同研究之间,模拟器指标和术中指标的开发与确定差异很大。几项研究采用了基于专家共识的方法,如改良的德尔菲法,来制定性能指标。对所有指标进行了内容效度、结构效度和预测效度评估。两项研究能够证明预测效度;然而,虚拟现实模拟器指标与术中评分之间的相关性有限。本评价强调了缺乏针对机器人子宫切除术的标准化和经过验证的指标,以及现有评估工具无法区分机器人手术技能水平。这为IMRA目前正在开展的工作提供了背景,即开发一种详细的评估工具,作为机器人子宫切除术课程的一部分来评估技能习得情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6c2/12165868/7177e50e8820/11701_2025_2471_Fig1_HTML.jpg

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