Subjective and objective results 1 year after robotic sacrocolpopexy using a lightweight Y-mesh.

INTRODUCTION AND HYPOTHESIS: The objective of this study was to assess outcomes following robotic sacrocolpopexy using a lightweight polypropylene Y-mesh. METHODS: During our study period, all patients who underwent robotic sacrocolpopexy were enrolled in this single-arm prospective trial. Endpoints included Pelvic Organ Prolapse Quantification (POP-Q) values; Pelvic Floor Distress Inventory, short form 20 (PFDI-20); Pelvic Floor Impact Questionnaire, short form 7 (PFIQ-7); Surgical Satisfaction scores; and the Sandvik Incontinence Severity Index. All surgeries were performed with a pre-configured monofilament type 1 polypropylene Y-mesh (Alyte©, C.R. Bard, Covington, GA, USA). Cure rates at 12 months were calculated using two separate definitions: (1) "clinical cure": no POP-Q points > 0, point C ≤ -5, no prolapse symptoms on the PFDI-20, and no reoperations for prolapse and (2) "objective anatomic cure": POP-Q stage 0 or 1, point C of ≤ -5, and no reoperations for prolapse. RESULTS: A total of 150 patients underwent robotic sacrocolpopexy and 143 (95 %) were available for 12-month follow-up. Mean age was 58.6 ± 9.8 and mean body mass index was 26.3 ± 4.5. Mean operative time and blood loss were 148 ± 27.6 min (range 75-250 min) and 51.2 ± 32, respectively. There were no mesh erosions or exposures, and mesh edges were not palpable in any patient. At 12 months the clinical cure rate was 95 %, and the objective anatomic cure rate was 84 %. The PFDI-20 mean score improved from 98 at baseline to 17 at 12 months (p < 0.0001); PFIQ-7 scores improved from 59 to 6.5 (p < 0.0001). CONCLUSIONS: Robotic sacrocolpopexy using this lightweight polypropylene Y-mesh offers excellent subjective and objective results at 1 year.

Predictive validity of a training protocol using a robotic surgery simulator.

BACKGROUND: Robotic surgery simulation may provide a way for surgeons to acquire specific robotic surgical skills without practicing on live patients. METHODS: Five robotic surgery experts performed 10 simulator skills to the best of their ability, and thus, established expert benchmarks for all parameters of these skills. A group of credentialed gynecologic surgeons naive to robotics practiced the simulator skills until they were able to perform each one as well as our experts. Within a week of doing so, they completed robotic pig laboratory training, after which they performed supracervical hysterectomies as their first-ever live human robotic surgery. Time, blood loss, and blinded assessments of surgical skill were compared among the experts, novices, and a group of control surgeons who had robotic privileges but no simulator exposure. Sample size estimates called for 11 robotic novices to achieve 90% power to detect a 1 SD difference between operative times of experts and novices (α = 0.05). RESULTS: Fourteen novice surgeons completed the study-spending an average of 20 hours (range, 9.7-38.2 hours) in the simulation laboratory to pass the expert protocol. The mean operative times for the expert and novices were 20.2 (2.3) and 21.7 (3.3) minutes, respectively (P = 0.12; 95% confidence interval, -1.7 to 4.7), whereas the mean time for control surgeons was 30.9 (0.6) minutes (P < 0.0001; 95% confidence interval, 6.3-12.3). Comparisons of estimated blood loss (EBL) and blinded video assessment of skill yielded similar differences between groups. CONCLUSIONS: Completing this protocol of robotic simulator skills translated to expert-level surgical times during live human surgery. As such, we have established predictive validity of this protocol.