对基本人类操作资源的评估可预测输尿管镜检查的操作情况。

Assessment of basic human performance resources predicts performance of ureteroscopy.

作者信息

Matsumoto Edward D, Kondraske George V, Ogan Kenneth, Jacomides Lucas, Wilhelm David M, Pearle Margaret S, Cadeddu Jeffrey A

机构信息

Division of Urology, McMaster University, Hamilton, Ontario, Canada.

出版信息

Am J Surg. 2006 Jun;191(6):817-20. doi: 10.1016/j.amjsurg.2005.07.043.

DOI:10.1016/j.amjsurg.2005.07.043

PMID:16720156

Abstract

BACKGROUND

Our objective was to predict endoscopic performance in a cadaver model using basic performance resources (BPRs) measurements.

METHODS

Medical students (n = 16) underwent intense ureteroscopic training on a virtual reality ureteroscopy trainer and were rated on performing ureteroscopy on a cadaver. The medical students also underwent 13 validated BPR measurements. Urology residents also performed cadaveric ureteroscopy and BPRs. A predictive model built from urology residents' (n = 16) BPRs and performance assessment was used to predict medical student cadaveric ureteroscopy performance based on their BPRs alone.

RESULTS

The predictive model built with urology residents predicted the ureteroscopic performance of 10 of 16 medical students within 15% of their rated ureteroscopic performance on the cadaver.

CONCLUSIONS

A predictive model built with urology residents can moderately predict the ureteroscopic performance of medical students from BPRs. Additional in vivo evaluation is required.

摘要

背景

我们的目标是使用基本性能资源（BPRs）测量来预测尸体模型中的内镜操作性能。

方法

16名医学生在虚拟现实输尿管镜训练器上接受强化输尿管镜训练，并在尸体上进行输尿管镜操作时接受评分。医学生还接受了13项经过验证的BPR测量。泌尿外科住院医师也进行了尸体输尿管镜检查和BPR测量。基于泌尿外科住院医师（16名）的BPR和性能评估建立的预测模型，仅根据医学生的BPR来预测其尸体输尿管镜操作性能。