European Society of Coloproctology: Guidelines for diagnosis and treatment of cryptoglandular anal fistula.

AIM: The primary aim of the European Society of Coloproctology (ESCP) Guideline Development Group (GDG) was to produce high-quality, evidence-based guidelines for the management of cryptoglandular anal fistula with input from a multidisciplinary group and using transparent, reproducible methodology. METHODS: Previously published methodology in guideline development by the ESCP has been replicated in this project. The guideline development process followed the requirements of the AGREE-S tool kit. Six phases can be identified in the methodology. Phase one sets the scope of the guideline, which addresses the diagnostic and therapeutic management of perianal abscess and cryptoglandular anal fistula in adult patients presenting to secondary care. The target population for this guideline are healthcare practitioners in secondary care and patients interested in understanding the clinical evidence available for various surgical interventions for anal fistula. Phase two involved formulation of the GDG. The GDG consisted of 21 coloproctologists, three research fellows, a radiologist and a methodologist. Stakeholders were chosen for their clinical and academic involvement in the management of anal fistula as well as being representative of the geographical variation among the ESCP membership. Five patients were recruited from patient groups to review the draft guideline. These patients attended two virtual meetings to discuss the evidence and suggest amendments. In phase three, patient/population, intervention, comparison and outcomes questions were formulated by the GDG. The GDG ratified 250 questions and chose 45 for inclusion in the guideline. In phase four, critical and important outcomes were confirmed for inclusion. Important outcomes were pain and wound healing. Critical outcomes were fistula healing, fistula recurrence and incontinence. These outcomes formed part of the inclusion criteria for the literature search. In phase five, a literature search was performed of MEDLINE (Ovid), PubMed, Embase (Ovid) and the Cochrane Database of Systematic Reviews by eight teams of the GDG. Data were extracted and submitted for review by the GDG in a draft guideline. The most recent systematic reviews were prioritized for inclusion. Studies published since the most recent systematic review were included in our analysis by conducting a new meta-analysis using Review manager. In phase six, recommendations were formulated, using grading of recommendations, assessment, development, and evaluations, in three virtual meetings of the GDG. RESULTS: In seven sections covering the diagnostic and therapeutic management of perianal abscess and cryptoglandular anal fistula, there are 42 recommendations. CONCLUSION: This is an up-to-date international guideline on the management of cryptoglandular anal fistula using methodology prescribed by the AGREE enterprise.

Meta-Analysis of the Impact of the Learning Curve in Robotic Rectal Cancer Surgery on Histopathologic Outcomes.

INTRODUCTION: Although the process of learning robotic surgery for rectal cancer is associated with a prolonged operating time and higher complication rates, its impact on histopathologic outcomes is unknown. The aim of this meta-analysis was to evaluate the impact of the learning curve in robotic surgery for rectal cancer on histopathologic outcomes. METHODS: The PubMed, EMBASE, Cochrane Library, MEDLINE via Ovid, CINAHL, and Web of Science databases were systematically searched. The inclusion criterion was any clinical study comparing the outcomes of robotic surgery for rectal cancer between different phases of the learning curve (LC) including competence (C). The primary endpoint was the circumferential resection margin (CRM) involvement rate defined as CRM ≤1 mm. The Mantel-Haenszel method with odds ratios with 95% confidence intervals (OR (95%CI)) was used for dichotomous variables. RESULTS: Ten studies including a total of 907 patients (521 LC and 386 C) were selected. Nine studies were found to have a low risk of bias, and one had a moderate risk of bias. The CRM involvement rate was 2.9% (13/441) for learning curve vs. 4.6% (13/284) for competence. This difference was not significant (OR (95%CI) = 0.70 (0.30, 1.60); p=0.39; I2=0%). CONCLUSION: A surgeon's learning curve seems to have no impact on CRM involvement rates compared to surgeon competence in robotic surgery for rectal cancer.

Learning curve for robotic-assisted laparoscopic 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.