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机器人辅助腹腔镜骶骨阴道(直肠)固定术的学习曲线:累积和分析。

Learning curve of robot-assisted laparoscopic sacrocolpo(recto)pexy: a cumulative sum analysis.

机构信息

Department of Gynecology, Amersfoort, The Netherlands; Twente University, Faculty of Electrical Engineering, Mathematics and Computer Science, Institute of Technical Medicine, Enschede, The Netherlands.

Department of Gynecology, Amersfoort, The Netherlands.

出版信息

Am J Obstet Gynecol. 2019 Nov;221(5):483.e1-483.e11. doi: 10.1016/j.ajog.2019.05.037. Epub 2019 May 29.

Abstract

BACKGROUND

Determination of the learning curve of new techniques is essential to improve safety and efficiency. Limited information is available regarding learning curves in robot-assisted laparoscopic pelvic floor surgery.

OBJECTIVE

The purpose of this study was to assess the learning curve in robot-assisted laparoscopic pelvic floor surgery.

STUDY DESIGN

We conducted a prospective cohort study. Consecutive patients who underwent robot-assisted laparoscopic sacrocolpopexy or sacrocolporectopexy were included (n=372). Patients were treated in a teaching hospital with a tertiary referral function for gynecologic/multicompartment prolapse. Procedures were performed by 2 experienced conventional laparoscopic surgeons (surgeons A and B). Baseline demographics were scored per groups of 25 consecutive patients. The primary outcome was the determination of proficiency, which was based on intraoperative complications. Cumulative sum control chart analysis allowed us to detect small shifts in a surgeon's performance. Proficiency was obtained when the first acceptable boundary line of cumulative sum control chart analysis was crossed. Secondary outcomes that were examined were shortening and/or stabilization of surgery time (measured with the use of cumulative sum control chart analysis and the moving average method).

RESULTS

Surgeon A performed 242 surgeries; surgeon B performed 137 surgeries (n=7 surgeries were performed by both surgeons). Intraoperative complications occurred in 1.9% of the procedures. The learning curve never fell below the unacceptable failure limits and stabilized after 23 of 41 cases. Proficiency was obtained after 78 cases for both surgeons. Surgery time decreased after 24-29 cases in robot-assisted sacrocolpopexy (no distinct pattern for robot-assisted sacrocolporectopexy). Limitations were the inclusion of 2 interventions and concomitant procedures, which limited homogeneity. Furthermore, analyses treated all complications in cumulative sum as equal weight, although there are differences in the clinical relevance of complications.

CONCLUSION

After 78 cases, proficiency was obtained. After 24-29 cases, surgery time stabilized for robot-assisted sacrocolpopexy. In this age of rapidly changing surgical techniques, it can be difficult to determine the learning curve of each procedure. Cumulative sum control chart analysis can assist with this determination and prove to be a valuable tool. Training programs could be individualized to improve both surgical performance and patient benefits.

摘要

背景

确定新技术的学习曲线对于提高安全性和效率至关重要。关于机器人辅助腹腔镜盆底手术的学习曲线,相关信息有限。

目的

本研究旨在评估机器人辅助腹腔镜盆底手术的学习曲线。

研究设计

我们进行了一项前瞻性队列研究。纳入了在一家具有三级转诊功能的教学医院接受机器人辅助经阴道骶骨固定术或经阴道骶骨直肠固定术的连续患者(n=372)。手术由 2 名经验丰富的传统腹腔镜外科医生(外科医生 A 和 B)进行。根据每组 25 例连续患者的情况对基线人口统计学数据进行评分。主要结局是根据术中并发症确定熟练程度。累积和控制图分析允许我们检测到外科医生表现的小变化。当累积和控制图分析的第一条可接受边界线被跨越时,即可获得熟练程度。检查的次要结局是手术时间的缩短和/或稳定(使用累积和控制图分析和移动平均方法进行测量)。

结果

外科医生 A 进行了 242 例手术;外科医生 B 进行了 137 例手术(n=7 例手术由两位外科医生共同进行)。1.9%的手术中发生了术中并发症。学习曲线从未低于不可接受的失败界限,并在 41 例中的 23 例后稳定下来。两位外科医生均在 78 例时获得了熟练程度。机器人辅助经阴道骶骨固定术的手术时间在 24-29 例后减少(机器人辅助经阴道骶骨直肠固定术无明显模式)。局限性在于包括 2 种干预措施和伴随手术,这限制了同质性。此外,尽管并发症的临床相关性不同,但累积和分析将所有并发症同等对待。

结论

在 78 例之后,获得了熟练程度。在 24-29 例之后,机器人辅助经阴道骶骨固定术的手术时间稳定。在这个外科技术迅速变化的时代,确定每个手术的学习曲线可能具有挑战性。累积和控制图分析可以辅助这种确定,并被证明是一种有价值的工具。培训计划可以个体化,以提高手术效果和患者受益。

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