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在机器人结直肠手术中获得手术能力的学习曲线。

The learning curve to attain surgical competency in robotic colorectal surgery.

作者信息

Wong Shing Wai, Ang Zhen Hao, Crowe Philip

机构信息

Department of General Surgery, Prince of Wales Hospital, Sydney, New South Wales, Australia.

Prince of Wales Clinical School, The University of New South Wales, Sydney, New South Wales, Australia.

出版信息

ANZ J Surg. 2022 May;92(5):1117-1124. doi: 10.1111/ans.17449. Epub 2022 Jan 4.

DOI:10.1111/ans.17449
PMID:34984787
Abstract

INTRODUCTION

The aim of the study was to assess the robotic colorectal surgery (RCS) learning curve of an experienced surgeon.

METHODS

A retrospective review of 117 consecutive patients who underwent total RCS at a single institution between October 2018 and July 2021 was performed. Patient demographics, surgery indications, operation type, intraoperative data, histopathology, morbidity and mortality, and length of stay were analysed. Cumulative summation technique (CUSUM) was used to construct a learning curve of surgeon console and total operation times (SCT and TOT).

RESULTS

There was no open conversion, positive resection margin and mortality in the study population. There were four Clavien-DIndo grade III complications and one local recurrence. The range for SCT was 18-855 min (mean 214, median 211) and TOT was 68-937 min (mean 302, median 291). The SCT CUSUM graph identified change in slope at cases 44 and 88, which divided the learning curve into three distinct phases. Patient demographics were similar through the three phases. There was proportionally more cancer cases performed in the first phase (P = 0.001). The mean SCT was significantly higher in Phase 2 when compared with Phases 1 and 3 (P = 0.03). The failure rate was similar through the three phases. There was a non-significant steady decline in LOS over the three phases, from 6.9 to 6.1 days.

CONCLUSION

Experienced colorectal surgeons can perform robotic surgery safely, even on patients with high complexity early in the learning curve. Audit of patient outcome should be an important component of learning curve assessment.

摘要

引言

本研究的目的是评估一位经验丰富的外科医生的机器人结直肠手术(RCS)学习曲线。

方法

对2018年10月至2021年7月期间在单一机构接受全机器人结直肠手术的117例连续患者进行回顾性研究。分析了患者的人口统计学资料、手术指征、手术类型、术中数据、组织病理学、发病率和死亡率以及住院时间。采用累积求和技术(CUSUM)构建外科医生控制台操作时间和总手术时间(SCT和TOT)的学习曲线。

结果

研究人群中无中转开腹、切缘阳性及死亡病例。有4例Clavien-DindoⅢ级并发症和1例局部复发。SCT范围为18 - 855分钟(平均214分钟,中位数211分钟),TOT为68 - 937分钟(平均302分钟,中位数291分钟)。SCT的CUSUM图在第44例和第88例病例时确定了斜率变化,将学习曲线分为三个不同阶段。三个阶段的患者人口统计学资料相似。第一阶段进行的癌症病例比例相对较高(P = 0.001)。与第1阶段和第3阶段相比,第2阶段的平均SCT显著更高(P = 0.03)。三个阶段的失败率相似。三个阶段的住院时间从6.9天到6.1天呈非显著的稳定下降。

结论

经验丰富的结直肠外科医生即使在学习曲线早期对高复杂性患者也能安全地进行机器人手术。对患者预后的审核应是学习曲线评估的重要组成部分。

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