Learning curve of robotic colectomy: a systematic review and meta-analysis of surgical proficiency, outcomes, and training protocols.

UNLABELLED

This investigation systematically evaluates the skill acquisition process in robotic colectomy procedures, determining the case volume required for surgical competency and assessing the effectiveness of various training methodologies. A comprehensive evidence synthesis was performed according to PRISMA standards. Multiple medical databases (PubMed, Embase, Cochrane Library) were systematically interrogated for relevant publications from January 2000 to January 2024. Eligible studies documented proficiency development in robotic colectomy, providing metrics on procedure duration, adverse events, and educational approaches. Analytical methods incorporated random-effects modeling with heterogeneity evaluation through I indices.

METHODS

From an initial pool of 1,800 potential studies, 35 met rigorous inclusion criteria, collectively representing 7500 surgical cases.

RESULTS

Proficiency development required between 20 and 70 procedures, with a weighted mean of 45 cases (95% confidence interval: 40-50). Significant reductions in operative duration (p < 0.001) and complication frequency (25% to 10%, p = 0.005) were observed following competency attainment. Training methodologies demonstrated considerable variation, with case volume requirements (designated TR-100 to TR-500) showing differential effectiveness. Formalized instructional programs incorporating simulation training and expert supervision correlated with accelerated skill acquisition.

CONCLUSION

achieving technical proficiency in robotic colectomy typically necessitates approximately 45 cases, with measurable enhancements in both procedural efficiency and clinical outcomes. The implementation of systematic training frameworks, particularly those integrating simulation components and mentored practice, appears crucial for optimizing surgical education.