Learning curve of robotic-assisted transabdominal preperitoneal repair (rTAPP) for inguinal hernias
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and Other Interventional Techniques
Learning curve of robotic‑assisted transabdominal preperitoneal repair (rTAPP) for inguinal hernias Francesco Proietti1 · Davide La Regina2 · Ramon Pini2 · Matteo Di Giuseppe2 · Agnese Cianfarani2 · Francesco Mongelli1 Received: 2 July 2020 / Accepted: 15 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Background Learning curves describe the rate of performance improvements according to the surgeon’s caseload, followed by a plateau where limited additional improvements are observed. The aim of this study was to evaluate the learning curve for robotic-assisted transabdominal preperitoneal repair (rTAPP) for inguinal hernias in surgeons already experienced in laparoscopic TAPP. Methods The study was approved by local ethic committee. Male patients undergoing rTAPP for inguinal hernia from October 2017 to December 2019 at the Bellinzona Regional Hospital were selected from a prospective database. Demographic and clinical data, including operative time, conversion to laparoscopic or open surgery, intra- and postoperative complications were collected and analyzed. Results Over the study period, 170 rTAPP were performed by three surgeons in 132 patients, and mean age was 60.1 ± 13.7 years. The cumulative summation (CUSUM) test showed a significant operative time reduction after the 4 3rd operation, once the 90% proficiency on the logarithmic tendency line was achieved. The corrected operative time resulted 71.1 ± 22.0 vs. 60.8 ± 13.5 min during and after the learning curve (p = 0.011). Only one intraoperative complication occurred during the learning curve and required an orchiectomy. Postoperatively, three complications (one seroma, one hematoma, and one mesh infection) required invasive interventions during the learning curve, while no cases were recorded after it (p = 0.312). Conclusion Our study shows that the rTAPP, performed by experienced laparoscopists, has a learning curve which requires 43 inguinal hernia repairs to achieve 90% proficiency and to significantly reduce the operative time. Keywords Robotic · Inguinal · Hernia · Groin · Learning curve · TAPP The learning curve (LC) can be applied in medicine to describe the rate of progress in gaining experience or new skills [1]. Surgeons typically exhibit improvements in performance over time, followed by a plateau where minimal/ limited additional improvements are observed [1]. Generally, surgical LCs are measured as a change in an operative variable (which can be considered a surrogate of surgeons’ performance) over a series of procedures. Studies investigating LCs for surgical procedures are of utmost importance, as * Francesco Proietti [email protected] 1
Surgery, Ospedale Regionale di Lugano, via Tesserete 46, 6900 Lugano, Switzerland
Surgery, Ospedale Regionale di Bellinzona e Valli, Via Ospedale 12, 6500 Bellinzona, Switzerland
2
LCs have substantial impact on surgical metrics, clinical outcomes, surgical teaching, and cost–benefit decisions [2, 3]
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