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[机器人辅助妇科肿瘤手术学习曲线的新方法]

[New approach of learning curve for robotic-assisted gynecologic oncology surgery].

作者信息

Yaribakht S, Guillemin F, Harter V, Malartic C, Marchal F

机构信息

Département de chirurgie, institut de cancérologie de Lorraine-Alexis-Vautrin, université de Lorraine, 6, avenue de bourgogne, CS 30519, 54519 Vandœuvre-lès-Nancy cedex, France.

Département de chirurgie, institut de cancérologie de Lorraine-Alexis-Vautrin, université de Lorraine, 6, avenue de bourgogne, CS 30519, 54519 Vandœuvre-lès-Nancy cedex, France.

出版信息

Gynecol Obstet Fertil. 2015 May;43(5):348-55. doi: 10.1016/j.gyobfe.2015.02.004. Epub 2015 Mar 23.

Abstract

OBJECTIVES

Define the phases composing the learning curve of total hysterectomy (TH) and radical hysterectomy with pelvic lymphadenectomy (RHPL) robot-assisted performed by a single surgeon with no prior experience in laparoscopic surgery.

METHODS

We retrospectively analyzed 72 procedures (TH, n=34 and RHPL, n=38) conducted between 2002 and 2011. The surgeon console time (CT) was used to determine the learning curve of TH and RHPL using CUSUM analysis. Epidemiological data, perioperative and postoperative complications were compared from the different phases of the learning curve.

RESULTS

CUSUM analysis of surgeon console time (CUSUMCT) identified two learning phases for the TH group (phase 1: initial learning, phase 2: surgical skill increase). For the RHPL group, three learning phases were identified (phase 1: initial learning, phase 2: extending surgical indications, phase 3: control of surgical skills). Perioperative and postoperative complication rates did not differ significantly between the learning phases. Surgeon CT decreased from the 9th case (P=0.01) for the TH group and from the 13th case (P=0.04) for the RHPL group.

DISCUSSION

CUSUM analysis of the learning curve in robotic-assisted gynecologic oncology surgery identified two phases of learning curve for simple procedures such as total hysterectomy and three phases for more complex procedures as radical hysterectomy with pelvic lymphadenectomy.

摘要

目的

确定由一名此前无腹腔镜手术经验的外科医生实施的机器人辅助全子宫切除术(TH)及根治性子宫切除术加盆腔淋巴结清扫术(RHPL)学习曲线的组成阶段。

方法

我们回顾性分析了2002年至2011年间进行的72例手术(TH,n = 34;RHPL,n = 38)。使用累积和分析(CUSUM分析)通过外科医生控制台时间(CT)来确定TH和RHPL的学习曲线。比较了学习曲线不同阶段的流行病学数据、围手术期和术后并发症。

结果

对外科医生控制台时间的累积和分析(CUSUMCT)确定TH组有两个学习阶段(阶段1:初始学习,阶段2:手术技能提高)。对于RHPL组,确定了三个学习阶段(阶段1:初始学习,阶段2:扩大手术适应症,阶段3:手术技能控制)。学习阶段之间围手术期和术后并发症发生率无显著差异。TH组从第9例病例开始外科医生CT下降(P = 0.01),RHPL组从第13例病例开始下降(P = 0.04)。

讨论

机器人辅助妇科肿瘤手术学习曲线的累积和分析确定,对于全子宫切除术等简单手术,学习曲线有两个阶段,而对于根治性子宫切除术加盆腔淋巴结清扫术等更复杂手术,学习曲线有三个阶段。

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