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机器人活体供体右半肝切除术的学习曲线:两个专业中心的结果分析

The learning curve for robotic living donor right hepatectomy: Analysis of outcomes in 2 specialized centers.

作者信息

Cheah Yee L, Yang Hye Yeon, Simon Caroline J, Akoad Mohamed E, Connor Ashton A, Daskalaki Despoina, Han Dai Hoon, Brombosz Elizabeth W, Kim Jae K, Tellier Maureen A, Ghobrial R Mark, Gaber A Osama, Choi Gi Hong

机构信息

Department of Surgery, JC Walter Jr Transplant Center, Houston Methodist Hospital, Houston, Texas, USA.

Department of Surgery, Division of Hepato-Biliary-Pancreatic Surgery and Liver Transplantation, Ajou University School of Medicine, Suwon, South Korea.

出版信息

Liver Transpl. 2025 Feb 1;31(2):190-200. doi: 10.1097/LVT.0000000000000480. Epub 2024 Oct 24.

DOI:10.1097/LVT.0000000000000480
PMID:39441028
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11732260/
Abstract

Robotic surgery is an emerging minimally invasive option for living donor hepatectomy. Currently, there are no studies on the learning curve of robotic donor hepatectomy. Thus, we evaluated the learning curve for robotic donor right hepatectomy. We retrospectively reviewed prospectively collected data from consecutive living donors who underwent robotic hepatectomy at 2 specialized centers between 2016 and 2022. We estimated the number of cases required to achieve stable operating times for robotic donor right hepatectomy using cumulative sum (CUSUM) analysis. The complication rates were similar between the 2 centers (22.8% vs. 26.7%; p = 0.74). Most complications were graded as minor (70.4%). Analysis of the total operative time demonstrated that the learning curves reached a peak at the 17th case in center 1 and the 9th case in center 2. The average operation times for cases 1-17 versus 18-99 in center 1 were 603 versus 438 minutes ( p < 0.001), and cases 1-9 versus 10-15 in center 2 were 532 versus 418 minutes ( p = 0.002). Complication rates were lower after the learning curves were achieved, although this did not reach statistical significance. A comparison of outcomes between centers suggests that a standardized approach to this complex operation can be successfully transferred.

摘要

机器人手术是活体供肝肝切除术一种新兴的微创选择。目前,尚无关于机器人供肝肝切除术学习曲线的研究。因此,我们评估了机器人供体右半肝切除术的学习曲线。我们回顾性分析了2016年至2022年期间在2个专业中心接受机器人肝切除术的连续活体供体的前瞻性收集数据。我们使用累积和(CUSUM)分析估计了实现机器人供体右半肝切除术稳定手术时间所需的病例数。两个中心的并发症发生率相似(22.8%对26.7%;p = 0.74)。大多数并发症为轻度(70.4%)。对总手术时间的分析表明,学习曲线在中心1的第17例和中心2的第9例达到峰值。中心1中第1 - 17例与第18 - 99例的平均手术时间分别为603分钟和438分钟(p < 0.001),中心2中第1 - 9例与第10 - 15例的平均手术时间分别为532分钟和418分钟(p = 0.002)。达到学习曲线后并发症发生率较低,尽管这未达到统计学显著性。中心间结果的比较表明,这种复杂手术的标准化方法可以成功转移。

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本文引用的文献

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CUSUM learning curves: what they can and can't tell us.CUSUM 学习曲线:它们能告诉我们什么,不能告诉我们什么。
Surg Endosc. 2023 Oct;37(10):7991-7999. doi: 10.1007/s00464-023-10252-1. Epub 2023 Jul 17.
2
The learning curve of the robotic-assisted lobectomy-a systematic review and meta-analysis.机器人辅助肺叶切除术的学习曲线——一项系统评价和荟萃分析
Ann Cardiothorac Surg. 2023 Jan 31;12(1):1-8. doi: 10.21037/acs-2022-urats-14. Epub 2023 Jan 14.
3
Implementation of a standardized surgical technique in robot-assisted restorative rectal cancer resection: a single center cohort study.
机器人辅助保肛直肠癌根治术中标准化手术技术的实施:单中心队列研究。
BMC Surg. 2022 Oct 13;22(1):360. doi: 10.1186/s12893-022-01809-3.
4
Robotic vs. laparoscopic liver surgery: a single-center analysis of 600 consecutive patients in 6 years.机器人与腹腔镜肝手术:6 年 600 例连续患者的单中心分析。
Surg Endosc. 2022 Aug;36(8):5854-5862. doi: 10.1007/s00464-021-08770-x. Epub 2022 May 31.
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Robotic surgery and liver transplantation: A single-center experience of 501 robotic donor hepatectomies.机器人手术和肝移植:501 例机器人供肝切除术的单中心经验。
Hepatobiliary Pancreat Dis Int. 2022 Aug;21(4):334-339. doi: 10.1016/j.hbpd.2022.05.006. Epub 2022 May 18.
6
Influence of surgical technique in donor hepatectomy on immediate and short-term living donor outcomes - A systematic review of the literature, meta-analysis, and expert panel recommendations.供肝切除术的手术技术对活体供者近期及短期结局的影响——文献系统评价、荟萃分析及专家小组建议
Clin Transplant. 2022 Oct;36(10):e14703. doi: 10.1111/ctr.14703.
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Monitoring surgical quality: the cumulative sum (CUSUM) approach.监测手术质量:累积和(CUSUM)方法。
Mediastinum. 2020 Mar 25;4:4. doi: 10.21037/med.2019.10.01. eCollection 2020.
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