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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dirros.openscience.si/IzpisGradiva.php?id=31184"><dc:title>Safe implementation of robotic colorectal surgery</dc:title><dc:creator>Košir,	Jurij Aleš	(Avtor)
	</dc:creator><dc:creator>Petrič,	Miha	(Avtor)
	</dc:creator><dc:creator>Trotovšek,	Blaž	(Avtor)
	</dc:creator><dc:creator>Norčič,	Gregor	(Avtor)
	</dc:creator><dc:creator>Grosek,	Jan	(Avtor)
	</dc:creator><dc:subject>robotic colorectal surgery</dc:subject><dc:subject>learning curve</dc:subject><dc:subject>safe implementation</dc:subject><dc:subject>complications</dc:subject><dc:description>Background: Robotic platforms expand minimally invasive options in colorectal surgery but raise concerns about training and patient safety. Dual-console systems may enable realtime coaching while preserving outcomes. Methods: We implemented a structured framework for safe implementation of robotic colorectal surgery that balances trainee autonomy with patient safety using a dual-console model. Early cases emphasized low-complexity pathology with escalation by predefined benchmarks. We prospectively gathered data and evaluated early program outcomes with primary endpoints including intraoperative adverse events, conversion to open surgery, 30-day morbidity, anastomotic integrity, and oncologic quality metrics. Secondary endpoints included operative time. Results: We included the analysis of 17 patients operated by one surgeon under supervision and compared the results to other senior colorectal surgeons. Out of the 17 patients, there were no conversions or anastomotic leaks. Overall complications were comparable to baseline robotic cases. Resection margins and lymph node yields met oncologic standards. Operative times were longer during early adoption but approached baseline with progression. Operative times were significantly reduced after eight cases and approached the times of senior surgeons after 13 cases. Conclusions: A dual-console strategy enables safe, scalable training in robotic colorectal surgery without compromising short-term patient outcomes or oncologic quality. Key elements include rigorous case selection, proficiency-based progression, real-time coaching, standardized protocols, and continuous data surveillance. This framework can guide institutions seeking to expand robotic colorectal programs while safeguarding patients and accelerating the learning curve.</dc:description><dc:date>2026</dc:date><dc:date>2026-07-20 10:49:03</dc:date><dc:type>Neznano</dc:type><dc:identifier>31184</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
