Learning curve analysis of robot-assisted minimally invasive esophagectomy

doi:10.3877/cma.j.issn.2095-8773.2019.01.013

Abstract

Abstract:

With the rapid development of DaVinci robot technology worldwide, it has been applied as a minimally invasive approach for esophagectomy in recent years. Despite the broad prospects of this type of surgery, it also brought greater challenge to thoracic surgeons. Until now, there are few reports on the DaVinci robotic system for esophagectomy , even fewer on its learning curve. The aim of this study was to summarize the research reports and explore the characteristics of learning curve for robot-assisted minimally invasive esophagectomy(RAMIE), which can be applied to guide the application of robotic surgery.

Key words: Esophageal cancer, Robot-assisted minimally invasive esophagectomy, Learning curve

Yang Yang, Xufeng Guo, bin Li, Xiaobing Zhang, Teng Mao, Yifeng Sun, Zhigang Li. Learning curve analysis of robot-assisted minimally invasive esophagectomy[J]. Chinese Journal of Thoracic Surgery(Electronic Edition), 2019, 06(01): 63-67.

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References 25

1	刘晟，仇明，江道振，等. 微创手术学习曲线的新概念与临床意义[J]. 中国微创外科杂志，2008, 8(1): 5-6.
2	Hernandez JM, Dimou F, Weber J, et al. Defining the learning curve for robotic-assisted esophagogastrectomy[J]. J Gastrointest Surg, 2013, 17(8): 1346-1351.
3	Kunisaki C, Makino H, Yamamoto N, et a1. Learning curve for laparoscopy-assisted distal gastrectomy with regional lymph node dissection for early gastric cancer[J]. Surg Laparosc Endosc Percutan Tech, 2008, 18(3): 236-241.
4	Kim MC, Jung GJ, Kim HH. Learning curve of laparoscopy-assisted distal gastrectomy with systemic lymphadenectomy for early gastric cancer[J]. World J Gastroenterol, 2005, 11(47): 7508-7511.
5	Abbott A, Shridhar R, Hoffe S, et al. Robotic assisted Ivor Lewis esophagectomy in the elderly patient[J]. J Gastrointest Oncol, 2015, 6(1): 31-38
6	Sarkaria IS, Rizk NP, Grosser R, et al. Attaining Proficiency in Robotic-Assisted Minimally Invasive Esophagectomy While Maximizing Safety During Procedure Development[J]. Innovations (Phila), 2016, 11(4): 268-273.
7	Grimminger PP, Tagkalos E, Hadzijusufovic E, et al. Change from hybrid to fully minimally invasive and robotic esophagectomy is possible without compromises[J]. Thorac Cardiovasc Surg, 2018. doi: 10.1055/s-0038-1670664.
8	Park SY, Kim DJ, Kang DR, et al. Learning curve for robotic esophagectomy and dissection of bilateral recurrent laryngeal nerve nodes for esophageal cancer[J]. Dis Esophagus, 2017, 30(12): 1-9.
9	Park S, Hyun K, Lee HJ, et al. A study of the learning curve for robotic oesophagectomy for oesophageal cancer[J]. Eur J Cardiothorac Surg, 2018, 53(4): 862-870.
10	van der Sluis PC, Ruurda JP, van der Horst S, et al. Learning Curve for Robot-Assisted Minimally Invasive Thoracoscopic Esophagectomy: Results From 312 Cases[J]. Ann Thorac Surg, 2018, 106(1): 264-271.
11	杨煜，张晓彬，孙益峰，等. 机器人辅助食管癌的微创外科切除：上海市胸科医院75例临床报道[J]．中华胸部外科电子杂志，2016, 3(3): 151-155.
12	Zhang H, Chen L, Wang Z, et al. The Learning Curve for Robotic McKeown Esophagectomy in Patients with Esophageal Cancer[J]. Ann Thorac Surg, 2018, 105(4): 1024-1030.
13	刘小龙，熊磊，丛壮壮，等. 达芬奇机器人在食管癌根治术中学习曲线的研究[J]. 医学研究生学报，2018, 31(8): 831-834.
14	Ahlberg G, Kruuna O, Leijonmarck CE, et al. Is the learning curve for laparoscopic fundoplication determined by the teacher or the pupil? [J] Am J Surg, 2005, 189(2): 184-189.
15	稽武，胡新勇，黎介寿. 手术机器人的应用进展和前景展望[J]. 医学研究生学报，2010, 23(9): 994-998.
16	Schreuder HW, Wolswijk R, Zweemer RP, et al. Training and learning robotic surgery, time for a more structured approach: a systematic review[J]. BJOG, 2012, 119(2): 137-149.
17	Gurusamy K, Aggarwal R, Palanivelu L, et al. Systematic review of randomized controlled trials on the effectiveness of virtual reality training for laparoscopic surgery[J]. Br J Surg, 2008, 95(9): 1088-1097.
18	Kelly DC, Margules AC, Kundavaram CR, et al. Face, content, and construct validation of the da Vinci Skills Simulator[J]. Urology, 2012, 79(5): 1068-1072.
19	Abboudi H, Khan MS, Aboumarzouk O, et al. Current status of validation for robotic surgery simulators - a systematic review[J]. BJU Int, 2013, 111(2): 194-205.
20	Patel HRH, Linares A, Joseph JV. Robotic and laparoscopic surgery: cost and training[J]. Surg Oncol, 2009, 18(3): 242-246.
21	Schachner T, Bonaros N, Wiedemann D, et al. Training surgeons to perform robotically assisted totally endoscopic coronary surgery[J]. Ann Thorac Surg, 2009, 88(2): 523-527.
22	Rashid TG, Kini M, Ind TE. Comparing the learning curve for robotically assisted and straight stick laparoscopic procedures in surgical novices[J]. Int J Med Robot, 2010, 6(3): 306-310.
23	Arain NA, Dulan G, Hogg DC, et al. Comprehensive proficiency-based inanimate training for robotic surgery: reliability, feasibility, and educational benefit[J]. Surg Endosc, 2012, 26(10): 2740-2745.
24	Mirheydar H, Jones M, Koeneman KS, et al. Robotic surgical education: a collaborative approach to training postgraduate urologists and endourology fellows[J]. JSLS, 2009, 13(3): 287-292.
25	Marengo F, Larraín D, Babilonti L, et al. Learning experience using the double-console da Vinci surgical system in gynecology: a prospective cohort study in a University hospital[J]. Arch Gynecol Obstet, 2012, 285(2): 441-445.

作者	时间(年)	例数	胸部时间(min)	总手术时间(min)	术中出血量(ml)	淋巴结数(个)	喉返神经麻痹(%)	吻合口瘘(%)	学习曲线例数
Hernandez等^[2]	2013	52	—	442.4	—	—	—	1.9	20
Abbott等^[5]	2015	134	—	407	150	—	—	4	20
Sarkaria等^[6]	2016	100	—	370	398	24	4	6	30
杨煜，等[6]	2016	75	95.6	275.2	230.7	15.9	14.7	—	20
Park等^[8]	2017	33	—	350.33	428.18	46.5	33	3	20
Grimminger等^[7]	2018	25	250.6	410.2	—	25	—	12	16
Park等^[9]	2018	140	180	468	—	41	25	9.3	80
van Hillegersberg等^[10]	2018	312	170	375	360	22	9	21	70
Zhang等^[12]	2018	72	90	317.5	132.5	22.6	10.9	8.6	26
刘小龙，等^[13]	2018	60	65.7	299.7	292.5	20.5	10	5	20

作者	时间(年)	例数	胸部时间(min)	总手术时间(min)	术中出血量(ml)	淋巴结数(个)	喉返神经麻痹(%)	吻合口瘘(%)	学习曲线例数
Hernandez等^[2]	2013	52	—	442.4	—	—	—	1.9	20
Abbott等^[5]	2015	134	—	407	150	—	—	4	20
Sarkaria等^[6]	2016	100	—	370	398	24	4	6	30
杨煜，等[6]	2016	75	95.6	275.2	230.7	15.9	14.7	—	20
Park等^[8]	2017	33	—	350.33	428.18	46.5	33	3	20
Grimminger等^[7]	2018	25	250.6	410.2	—	25	—	12	16
Park等^[9]	2018	140	180	468	—	41	25	9.3	80
van Hillegersberg等^[10]	2018	312	170	375	360	22	9	21	70
Zhang等^[12]	2018	72	90	317.5	132.5	22.6	10.9	8.6	26
刘小龙，等^[13]	2018	60	65.7	299.7	292.5	20.5	10	5	20

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