肾部分切除术训练模型系统回顾

R. Farinha, E. Mazzone, Marco Paciotti, Alberto Breda, James Porter, Kris Maes, Ben Van Cleynenbreugel, Jozef Vander Sloten, Alexandre Mottrie, Anthony G. Gallagher
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引用次数: 0

摘要

机器人辅助肾部分切除术(PN)是一项复杂的指标性手术,泌尿科医生需要学习如何安全地进行手术。我们从 PubMed、Cochrane Library Central、EMBASE、MEDLINE 和 Scopus 数据库中提取并审查了从开始到 2023 年 4 月的数据,系统地评估了 PN 训练模型 (TM) 的开发和验证证据。证据水平采用牛津循证医学中心进行评估。在筛选出的 331 篇文章中,有 14 项队列研究被纳入分析。没有发现随机对照试验,所有研究的模型、研究小组、任务定义和所用指标的主观性都不尽相同。所有模型的真实性和作为培训工具的实用性都被评为良好。由于方法上的差异,因此无法就构建验证得出明确结论。没有关于辨别性或预测性验证证据的报告,也没有使用 TM 训练的实验组与对照组之间的比较。之前的研究结果表明,支持所述 TM 在掌握安全进行 PN 所需的技能方面的有效性的证据水平较低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic review on training models for partial nephrectomy
Robot-assisted partial nephrectomy (PN) is a complex and index procedure with a difficult learning curve that urologists need to learn how to perform safely. We systematically evaluated the development and validation evidence underpinning PN training models (TMs) by extracting and reviewing data from PubMed, Cochrane Library Central, EMBASE, MEDLINE, and Scopus databases from inception to April 2023. The level of evidence was assessed using the Oxford Center for Evidence-Based Medicine. Of the 331 screened articles, 14 cohort studies were included in the analysis. No randomized controlled trials were found, and the heterogeneous nature of the models, study groups, task definitions, and subjectivity of the metrics used were transversal to all studies. All the models were rated good for realism and usefulness as training tools. Methodological discrepancies preclude definitive conclusions regarding the construct validation. No discriminative or predictive validation evidence was reported, nor were there comparisons between an experimental group trained with a TM and a control group. The previous findings stand for the low level of evidence supporting the efficacy of the described TMs in the acquisition of skills required to safely perform PN.
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