Robotic colectomy with intracorporeal anastomosis is feasible with no operative conversions during the learning curve...

The benefits of performing a colectomy robotically instead of laparoscopically have not conclusively been demonstrated. Evaluation of studies is limited by sample size, retrospective design, heterogeneity of operative techniques, sparse adjustment for learning curve, and mixed results. Consequently, adoption of robotic colectomy by surgeons has been expectedly slow. The objectives of the study were to compare the outcomes of robotic colectomy to laparoscopic colectomy for patients with right-sided tumors undergoing a standardized completely intracorporeal operation and to examine the impact of prior experience with laparoscopic right colectomies on the performance of robotic right colectomies. Retrospective review of outcomes of consecutive patients undergoing a robotic right colectomy (robot) compared to those undergoing laparoscopic colectomy (LAP). LAP patients were further subdivided into a group during the learning curve (LC) and after the learning curve (post-LC). Data collected included operative time (OT), conversion to laparotomy, lymph nodes harvested (LN), length of stay (LOS), 30-day morbidity, and mortality. Comparison of continuous and categorical variables was assessed with the independent samples t test and Chi-square test, respectively. Data are expressed as mean ± SD, and significance defined as p < 0.05. 122 patients underwent robot (n = 21), LAP (n = 101), LC (n = 51), or post-LC (n = 50). OT was decreased for post-LC compared to LC (198 vs. 228 min). There were no conversions in robot and five with LAP. Morbidity was similar for robot (14%) compared to LAP (22%), LC (24%), or post-LC cases (20%). Median LOS was similar for robot vs. LAP (3 vs. 5 days). Robot had greater mean LN yield vs. LAP (19 vs. 14, p = 0.02). The initial outcomes with completely intracorporeal colectomy achieved robotically were equivalent to results during or after LC for laparoscopic resection. Proficiency gained with LAP seems to positively impact the initial results with the robot.