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使用机器人技能全球评估和二元评分指标进行机器人手术熟练程度评估的辨别力、可靠性、敏感性和特异性:一项随机对照试验的结果

Discrimination, Reliability, Sensitivity, and Specificity of Robotic Surgical Proficiency Assessment With Global Evaluative Assessment of Robotic Skills and Binary Scoring Metrics: Results From a Randomized Controlled Trial.

作者信息

De Groote Ruben, Puliatti Stefano, Amato Marco, Mazzone Elio, Larcher Alessandro, Farinha Rui, Paludo Artur, Desender Liesbeth, Hubert Nicolas, Cleynenbreugel Ben Van, Bunting Brendan P, Mottrie Alexandre, Gallagher Anthony G, Rosiello Giuseppe, Uvin Pieter, Decoene Jasper, Tuyten Tom, D'Hondt Mathieu, Chatzopoulos Charles, De Troyer Bart, Turri Filippo, Dell'Oglio Paolo, Liakos Nikolaos, Andrea Bravi Carlo, Lambert Edward, Andras Iulia, Di Maida Fabrizio, Everaerts Wouter

机构信息

From the ORSI Academy, Ghent, Belgium.

Department of Urology, OLV, Aalst, Belgium.

出版信息

Ann Surg Open. 2023 Aug 16;4(3):e307. doi: 10.1097/AS9.0000000000000307. eCollection 2023 Sep.

Abstract

OBJECTIVE

To compare binary metrics and Global Evaluative Assessment of Robotic Skills (GEARS) evaluations of training outcome assessments for reliability, sensitivity, and specificity.

BACKGROUND

GEARS-Likert-scale skills assessment are a widely accepted tool for robotic surgical training outcome evaluations. Proficiency-based progression (PBP) training is another methodology but uses binary performance metrics for evaluations.

METHODS

In a prospective, randomized, and blinded study, we compared conventional with PBP training for a robotic suturing, knot-tying anastomosis task. Thirty-six surgical residents from 16 Belgium residency programs were randomized. In the skills laboratory, the PBP group trained until they demonstrated a quantitatively defined proficiency benchmark. The conventional group were yoked to the same training time but without the proficiency requirement. The final trial was video recorded and assessed with binary metrics and GEARS by robotic surgeons blinded to individual, group, and residency program. Sensitivity and specificity of the two assessment methods were evaluated with area under the curve (AUC) and receiver operating characteristics (ROC) curves.

RESULTS

The PBP group made 42% fewer objectively assessed performance errors than the conventional group ( < 0.001) and scored 15% better on the GEARS assessment ( = 0.033). The mean interrater reliability for binary metrics and GEARS was 0.87 and 0.38, respectively. Binary total error metrics AUC was 97% and for GEARS 85%. With a sensitivity threshold of 0.8, false positives rates were 3% and 25% for, respectively, the binary and GEARS assessments.

CONCLUSIONS

Binary metrics for scoring a robotic VUA task demonstrated better psychometric properties than the GEARS assessment.

摘要

目的

比较二元指标和机器人技能全球评估(GEARS)对训练结果评估的可靠性、敏感性和特异性。

背景

GEARS Likert量表技能评估是机器人手术训练结果评估中广泛接受的工具。基于熟练度的进阶(PBP)训练是另一种方法,但使用二元性能指标进行评估。

方法

在一项前瞻性、随机、双盲研究中,我们比较了传统训练与PBP训练在机器人缝合、打结吻合任务中的效果。来自比利时16个住院医师培训项目的36名外科住院医师被随机分组。在技能实验室中,PBP组训练至展示出定量定义的熟练度基准。传统组的训练时间与之相同,但无熟练度要求。最终试验进行了视频记录,并由对个体、组和住院医师培训项目不知情的机器人外科医生使用二元指标和GEARS进行评估。通过曲线下面积(AUC)和受试者工作特征(ROC)曲线评估两种评估方法的敏感性和特异性。

结果

PBP组在客观评估的性能错误方面比传统组少42%(<0.001),在GEARS评估中得分高15%(=0.033)。二元指标和GEARS的平均评分者间信度分别为0.87和0.38。二元总误差指标的AUC为97%,GEARS为85%。在敏感性阈值为0.8时,二元评估和GEARS评估的假阳性率分别为3%和25%。

结论

用于评估机器人VUA任务的二元指标在心理测量特性方面优于GEARS评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a80/10513364/a1184db020c4/as9-4-e307-g001.jpg

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