Single-port versus multiport robotic colectomy for colonic neoplasia: short-term outcomes and learning-curve analysis.

BACKGROUND

Single-port (SP) robotic platforms have recently been introduced in colorectal surgery to further reduce surgical invasiveness. Evidence comparing SP and multiport (MP) robotic colectomy for colonic neoplasia in routine clinical practice remains limited, particularly regarding short-term outcomes and learning-curve dynamics.

METHODS

This retrospective single-centre study compared consecutive patients undergoing elective SP or MP da Vinci robotic colectomy for colonic neoplasia between July 2024 and October 2025. Short-term operative, postoperative, and early oncological outcomes were analysed. Group comparisons were performed using non-parametric tests, while univariate regression models explored associations between surgical approach and outcomes. A learning-curve analysis within the SP cohort assessed changes in docking time over consecutive cases.

RESULTS

Fifty-three patients were included (SP = 15; MP = 38), with comparable baseline characteristics. Docking time was shorter in the MP group (median SP 9 vs MP 7 min, p < 0.01), whereas overall operating time did not differ significantly (median 200 vs 227 min, p = 0.41). Conversion to open surgery occurred in 13.3% of SP and 2.6% of MP cases (p = 0.17). Major complications were observed in 6.7% of SP and 13.2% of MP patients (OR 0.47, 95% CI 0.02-3.29; p = 0.51). Length of hospital stay and early oncological parameters, including lymph node yield and resection margins, were comparable. Within the SP cohort, docking time decreased significantly with increasing experience (β - 0.76 min per case, 95% CI - 1.18 to - 0.40; p < 0.01).

CONCLUSIONS

In this real-world experience, SP robotic colectomy for colonic neoplasia achieved short-term outcomes comparable to the MP approach, without increased perioperative risk. A rapid learning curve for docking time supports the safe early implementation of SP robotic systems in centres with established robotic expertise.