Kevin K Sng, Dr, Masayasu Hara, Dr, Jae Won Shin, Dr, Byung Eun Yoo, Dr, Kyung-Sook Yang, Seon Hahn Kim, Dr
Division of Colorectal Surgery, Department of Surgery, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
Robotic rectal surgery is gaining popularity. We aimed to define the learning curve of an experienced laparoscopic colorectal surgeon in performing robotic rectal cancer surgery. We hypothesized that there are multiple phases in this learning process.
Methods and Procedures
This is a retrospective analysis of data from our colorectal database. Consecutive patients undergoing robotic rectal surgery between July 2007 and August 2011 were identified and placed in chronological order based on operation dates. The CUSUM (cumulative sum) technique was used to analyze the total operating, total robotic, console and docking times. We applied the process of model fitting on the CUSUMs as a fourth-order polynomial, to highlight the different phases in each chart. Pearson Chi-squared test, Fisher’s exact test, Independent Samples t test, One-way ANOVA, Kruskal Wallis test and the Mann-Whitney test were used as appropriate. P value of <0.05 was considered statistically significant.
We identified 197 patients who underwent robotic rectal resection. The median total operative, total robot, console and docking times (minutes) were 265 (145-515), 140 (59-367), 135 (50-360) and 5 (3-40) respectively. CUSUM analysis of docking time showed that the learning curve for robot docking was reached after 20 cases. CUSUM analysis of total operative, robot and console times demonstrated 3 phases. The first phase from case number 1 to 35 represented the initial learning curve. The second and third phases included cases 36 to 128, and 129 to 197 respectively. The second phase involved more technically challenging cases associated with an increase in operative time. The third phase represented the concluding phase in the learning curve when the operative time decreased and stabilised. Inter-phase comparisons of gender, age, BMI and ASA grading showed no significant differences. In comparing phase 1 with phase 2/3, we found parameters indicating the increased complexity of cases in the latter 2 phases. In phase 1, 45.7% of patients had their tumours within 7cm from the anal verge compared to 64.2% in phases 2/3 (p=0.042). Neoadjuvant chemo-radiotherapy was administered to 2.9% of phase 1 patients compared to 32.7% in phase 2/3 (p=0.000). Splenic flexure was mobilised in 8.6% of phase 1 patients compared to 56.8% in phase 2/3 (p=0.000). Median blood loss was under 50mls in all 3 phases. Between phases 1 and 2/3, there were no significant differences in median lymph nodes harvested (19 vs 15, p=ns) and median distal margin (1.8cm vs 1.7cm, p=ns) but the patients in phase 2/3 had a significantly longer hospital stay compared to those in phase 1 (9 days vs 8 days, p=0.002). No patients in phase 1 had Clavien-Dindo grade 3a/3b complications compared to 8.6% of patients in phase 2/3 (p=ns). Anastomotic leak rate was 5.7% in phase 1 and 10.5% in phase 2/3 (p=ns). Our conversion rate was 0.
At least 3 phases in the learning curve of robotic-assisted rectal surgery are defined for an experienced laparoscopic colorectal surgeon.
Session: Podium Presentation
Program Number: S033