Cumulative Sum Analysis of the Operator Learning Curve for Robot-Assisted Mayo Clinic Level I-IV Inferior Vena Cava Thrombectomy Associated with Renal Carcinoma: A Study of 120 Cases at a Single Center

机器人辅助下腔静脉血栓切除术治疗肾癌的梅奥诊所 I-IV 级手术操作者学习曲线的累积和分析:一项单中心 120 例病例研究

阅读:1

Abstract

BACKGROUND This study aimed to use cumulative sum analysis of the operator learning curve for robot-assisted Mayo Clinic level I-IV inferior vena cava (IVC) thrombectomy associated with renal carcinoma, and describes the development of an optimized operative procedure at a single center. MATERIAL AND METHODS A retrospective study included 120 patients with Mayo Clinic level I-IV IVC thrombus who underwent robotic surgery between 2013 and 2018. Points in the learning curve were identified using cumulative sum analysis, and their impact was assessed by multiple regression analysis. Perioperative indicators analyzed included operative time, estimated blood loss, early complications, and the 90-day progression rate. RESULTS Cumulative sum analysis identified three phases in the learning curve of robot-assisted IVC thrombectomy. The median operative time decreased from 265 min (range, 212-401 min) to 207 min (range, 146-276 min) (p=0.003), the median estimated blood loss decreased from 775 ml (range, 413-1500 ml) to 300 ml (range, 163-813 ml) (p=0.006), and the early complication rate decreased from 52.5% to 15.0% (p<0.001). Multivariate analysis showed that for an initial 40 cases and a further 80 cases, the learning phase, the affected side, the Mayo Clinic level, and the surgical method were independent factors that affected operative time, estimated blood loss, and the rate of early complications. CONCLUSIONS Experience from an initial 40 cases and a further 80 cases of Mayo Clinic level I-IV IVC thrombectomy associated with renal carcinoma were found to provide acceptable surgical and clinical outcomes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。