Experts vs super-experts: differences in automated performance metrics and clinical outcomes for robot-assisted radical prostatectomy
Experts vs super-experts: differences in automated performance metrics and clinical outcomes for robot-assisted radical prostatectomy
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DOI：
10.1111/bju.14599
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发表时间：
2019-05-01
影响因子：
4.5
通讯作者：
Gill, Inderbir S.
中科院分区：
文献类型：
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作者：
Hung, Andrew J.;Oh, Paul J.;Gill, Inderbir S.
目的评价机器人辅助根治性膀胱切除术（RARP）的四个基本步骤：膀胱颈清扫术、蒂清扫术、前列腺尖清扫术和膀胱尿道吻合术的自动化性能指标（APM）和专家和超级专家的临床数据。主题和方法我们在RARP期间捕获APM（运动跟踪和系统事件数据）并同步手术视频。在两个经验水平之间比较APM：专家（100-750例）和超级专家（2100-3500例）。然后比较两组的临床结局（围手术期、肿瘤学和功能）。使用多水平混合效应模型分析了125个RARP的APM和结果。结果超级专家在选择四个基本步骤时，与专家相比，差异有统计学意义（P < 0.05）。尽管PSA和Gleason评分相似，但超级专家在围手术期结局方面的临床表现优于专家，淋巴结产量分别为22.6 vs 14.9个（P < 0.01），失血量更少（分别为125 vs 130 mL; P < 0.01），30天时再入院率更低（分别为1% vs 13%; P = 0.02）。在肿瘤学和功能结局方面观察到类似但不显著的趋势，与专家相比，超级专家的生化复发率较低（分别为5%和15%; P = 0.13），3个月时的复发率较高（分别为36%和18%; P = 0.14）。结论我们发现，专家和超级专家在RARP的四个基本步骤中选择APM时存在显著差异，表明外科医生即使在获得专业知识后，也会继续提高性能。我们希望最终确定APM和临床结果之间的关联，以针对外科医生定制干预措施并优化患者结果。
Objectives To evaluate automated performance metrics (APMs) and clinical data of experts and super-experts for four cardinal steps of robot-assisted radical prostatectomy (RARP): bladder neck dissection; pedicle dissection; prostate apex dissection; and vesico-urethral anastomosis. Subjects and Methods We captured APMs (motion tracking and system events data) and synchronized surgical video during RARP. APMs were compared between two experience levels: experts (100-750 cases) and super-experts (2100-3500 cases). Clinical outcomes (peri-operative, oncological and functional) were then compared between the two groups. APMs and outcomes were analysed for 125 RARPs using multi-level mixed-effect modelling. Results For the four cardinal steps selected, super-experts showed differences in select APMs compared with experts (P < 0.05). Despite similar PSA and Gleason scores, super-experts outperformed experts clinically with regard to peri-operative outcomes, with a greater lymph node yield of 22.6 vs 14.9 nodes, respectively (P < 0.01), less blood loss (125 vs 130 mL, respectively; P < 0.01), and fewer readmissions at 30 days (1% vs 13%, respectively; P = 0.02). A similar but nonsignificant trend was seen for oncological and functional outcomes, with super-experts having a lower rate of biochemical recurrence compared with experts (5% vs 15%, respectively; P = 0.13) and a higher continence rate at 3 months (36% vs 18%, respectively; P = 0.14). Conclusion We found that experts and super-experts differed significantly in select APMs for the four cardinal steps of RARP, indicating that surgeons do continue to improve in performance even after achieving expertise. We hope ultimately to identify associations between APMs and clinical outcomes to tailor interventions to surgeons and optimize patient outcomes.