Search

Background: Faecal incontinence (FI) is both a medical and social problem, with an underestimated incidence. For patients with internal anal sphincter damage, implantation of biomaterial in the anal canal is a recognised treatment option. One such material, Gatekeeper™, has previously shown promising short- and medium-term results without any major complications, including displacement. The main aim of the present study is to assess the degree to which displacement of Gatekeeper prostheses may occur and to determine whether this is associated with patient outcomes. Methods: Seven patients (six females) with a mean age of 55.6 years [50.5-57.2] and a mean FI duration of 6 ± 2 years were prospectively enrolled in the study. Each subject was anaesthetised and underwent implantation of six prostheses in the intersphincteric region, guided by endoanal 3D ultrasound (3D-EAU). Follow-up was performed at post-interventional months 1, 3, and 12 (median 12 ± 4 months), during which data were obtained from a defaecation diary, Wexner scale assessment, anorectal manometry (ARM), 3D-EAU, and a health status and quality of life questionnaire (FIQL). Results: At 3-month follow-up, 3D-EAU revealed displacement of 24/42 prostheses in 5/7 patients. Of these, 15 had migrated to the lower portion and 9 to the upper portion of the anal canal and rectum. Despite this migration, treatment was considered successful in 3/7 patients. In one patient, it was necessary to remove a prosthesis due to spontaneous extrusion. Conclusions: We have shown that displacement of the Gatekeeper™ prosthesis occurs, but is not associated with poorer clinical outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Robotic-assisted rectal cancer surgery offers multiple advantages for surgeons, and it seems to yield the same clinical outcomes as regards the short-time follow-up of patients compared to conventional laparoscopy. This surgical approach emerges as a technique aiming at overcoming the limitations posed by rectal cancer and other surgical fields of difficult access, in order to obtain better outcomes and a shorter learning curve., Material and Methods: A systematic review of the literature of robot-assisted rectal surgery was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search was conducted in October 2015 in PubMed, MEDLINE and the Cochrane Central Register of Controlled Trials, for articles published in the last 10 years and pertaining the learning curve of robotic surgery for colorectal cancer. It consisted of the following key words: "rectal cancer/learning curve/robotic-assisted laparoscopic surgery"., Results: A total of 34 references were identified, but only 9 full texts specifically addressed the analysis of the learning curve in robot-assisted rectal cancer surgery, 7 were case series and 2 were non-randomised case-comparison series. Eight papers used the cumulative sum (CUSUM) method, and only one author divided the series into two groups to compare both. The mean number of cases for phase I of the learning curve was calculated to be 29.7 patients; phase II corresponds to a mean number 37.4 patients. The mean number of cases required for the surgeon to be classed as an expert in robotic surgery was calculated to be 39 patients., Conclusion: Robotic advantages could have an impact on learning curve for rectal cancer and lower the number of cases that are necessary for rectal resections.

Background: Robotic surgical management of rectal cancer has a series of advantages which might facilitate the surgical approach to the pelvic cavity and reduce conversion rates. The aim of the present study is to identify independent factors for conversion during robotic rectal cancer surgery., Methods: A total of 67 patients underwent preoperative CT scan in order to obtain a three-dimensional image of the pelvis, the tumour and prostate. We measured maximum and minimum ilio-iliac, sacral promontory-pubis, coccyx-pubis diameters and maximum lateral axis. Further variables under consideration were age, BMI and use of neoadjuvant therapy. We recorded short-term follow-up outcomes of the resected tumour., Results: The present study included 67 patients (39 males) with an average age of 65.11 ± 10.30 years and a BMI of 27.70 ± 3.97 kg/m(2). Operative procedures included nine abdominoperineal resections and 58 low anterior resections. There were 15 (22.38 %) conversions. Mean operating time was 192.2 ± 42.73 min. Minimum ilio-iliac, maximum ilio-iliac, promontory-pubic and coccyx-pubis diameter as well as maximum lateral axis were 100.38 ± 7.65, 107.10 ± 10.01, 109.97 ± 9.20, 105.61 ± 9.27 and 129.01 ± 9.94 mm, respectively. Mean tumour volume was 37.06 ± 44.08 cc; mean prostate volume was 42.07 ± 17.49 cc. The univariate analysis of the variables showed a correlation between conversion and BMI and minimum ilio-iliac and coccyx-pubis diameters (p = 0.004, 0.047, 0.046). In the multivariate analysis, the only independent predictive factor for conversion was the BMI (p = 0.004).No correlation was found between conversion and sex, age, tumour volume or the rest of pelvic diameters., Conclusion: BMI is an independent factor for conversion in robotic-assisted rectal cancer surgery.

Introduction: One of the main uses of robotic assisted abdominal surgery is the mesorectal excision in patients with rectal cancer. The aim of the present study is to analyse the learning curve for robotic assisted laparoscopic resection of rectal cancer., Patients and Methods: We included in our study 43 consecutive rectal cancer resections (16 females and 27 males) performed from January 2008 through December 2010. Mean age of patients was 66 ± 9.0 years. Surgical procedures included both abdomino-perineal and anterior resections. We analysed the following parameters: demographic data of the patients included in the study, intra- and postoperative data, time taking to set up the robot for operations (set-up or docking time), operative time, intra- and postoperative complications, conversion rates and pathological specimen features. The learning curve was analysed using cumulative sum (CUSUM) methodology., Results: The procedures understudied included seven abdomino-perineal resections and 36 anterior resections. In our series of patients, mean robotic set-up time was 62.9 ± 24.6 min, and the mean operative time was 197.4 ± 44.3 min. Once we applied CUSUM methodology, we obtained two graphs for CUSUM values (operating time and success), both of them showing three well-differentiated phases: phase 1 (the initial 9-11 cases), phase 2 (the middle 12 cases) and phase 3 (the remaining 20-22 cases). Phase 1 represents initial learning; phase 2 plateau represents increased competence in the use of the robotic system, and finally, phase 3 represents the period of highest skill or mastery with a reduction in docking time (p = 0.000), but a slight increase in operative time (p = 0.007)., Conclusion: The CUSUM curve shows three phases in the learning and use of robotic assisted rectal cancer surgery which correspond to the phases of initial learning of the technique, consolidation and higher expertise or mastery. The data obtained suggest that the estimated learning curve for robotic assisted rectal cancer surgery is achieved after 21-23 cases.