Omar Y Kudsi, MD, MBA, FACS, Katie Sean, MD, Rachel Goldstein. Tufts University School of Medicine
Limited data is available to assess the learning curve for robotic-assisted cholecystectomy. The aim of this study was to evaluate the learning curve for robotic-assisted cholecystectomy at a single institution.
This is a retrospective review of prospectively collected data between December 2012 and September 2014. A total of 260 Robotic Cholecystectomy were identified. Of these 260 cases 110 were elective cases while 115 were emergent cases completed in a multiport fashion. A total of 35 cases were completed via a single site approach. In order to study the learning curve for Robotic Cholecystectomy, we grouped the cases sequentially in groups of 25 cases. The mean Console time and mean Skin to Skin time for each consecutive series of 25 cases was calculated and graphed accordingly. We used ordinary least squares regression, with each series of 25 cases as an independent predictor of time.
Both Console and Skin to Skin time decreased over time with case experience. A significant downward trend in Console time and Skin to Skin time p<0.0001 and p=0.003 respectively were seen. In order to understand which factors influenced Skin to skin time, a regression model containing Age, Gender, Obesity, Comorbidities, Emergent versus Non-emergent presentation, Multiport versus Single Site approach, Acute versus Chronic pathology, Conversion, and case experience was run. Statistically significant predictors of Skin to Skin time were Gender, Acute versus Chronic pathology, conversions, case experience and comorbidities. Demographics were the following: (N=180) women and (N=80 ) men. Mean age was 52.49 years (20-89 years) with a mean BMI of 31.4 (18-71). Out of the 260 cases, (N=6) were converted to open cholecystectomies (2.3 %). Mean operative time was 69.41 Minutes (20-264 minutes); including mean console operative time was 41.5 (6-229 minutes) with mean EBL of 18 mL (2 -500 mL). Mean length of stay was 0.53 days (0-4 days).
A significant learning curve can be seen for Robotic Cholecystectomy. This learning curve is not influenced by the approach to Robotic cholecystectomy (Multiport or Single Site) nor by whether a case is emergent or non-emergent. The introduction of Single site cholecystectomy can be a natural transition for the Robotic surgeon performing multiport cholecystectomy and does not significantly increase the time taken to complete the case.