Learning Curve in Robot-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group

Gallioli, Andrea; Territo, Angelo; Boissier, R.; Campi, Riccardo; Vignolini, Graziano; Musquera, Mireía; Alcaraz, Antonio; Decaestecker, Karel; Tuğcu, Volkan; Vanacore, D.; Serni, Sergio; Breda, Alberto

doi:10.1016/j.eururo.2019.12.008

Cited by 64 publications

(51 citation statements)

References 22 publications

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“…Our experience confirms that RAKT achieved favorable intraoperative, peri-operative, and functional outcomes at both a short-and mid-term follow-up ( Table 2), as previously reported (6,26). In particular, the times required for arterial, venous and uretero-vesical anastomosis were at least noninferior to those reported in the literature for open KT (7,14), even considering the influence of our team's learning curve (6). Moreover, while the overall surgical morbidity of RAKT in our series was acceptable and comparable to the open KT series (14), most adverse events (including major complications and DGFs) occurred in the DD-RAKT cohort, suggesting a higher peri-operative risk for these patients ( Table 2).…”

Section: Discussionsupporting

confidence: 90%

“…Although RAKT is still being performed only at selected referral Centers worldwide, current evidence confirms is feasibility, safety and reproducibility (1,2,19,20). In fact, RAKT with regional hypothermia in the setting of "elective" living donation has been shown to achieve favorable short-and mid-term perioperative and functional outcomes (mirroring the principles of open KT) while providing the key advantages of minimallyinvasive surgery (2,3,6,8,(19)(20)(21)(22)(23). Moreover, recent studies demonstrated that RAKT can be safely performed by experienced robotic surgeons even in case of grafts with vascular anomalies (5) or complex recipients such as those with ADPKD (16) or morbid obesity (7,24,25).…”

Section: Discussionmentioning

confidence: 99%

“…Our surgical technique follows the principles of the Vattikuti Urology Institute-Medanta technique (1, 2) with specific technical nuances developed over time during the learning curve (4,6).…”

Section: Patient Positioning and Port Placementmentioning

confidence: 99%

“…To date, most groups performing RAKT replicated the Vattikuti-Medanta technique (1). Nevertheless, specific modifications have been proposed by several teams to adapt the technique to the availability of surgical instrumentation, logistical issues, and surgeon's preference during the learning curve (4)(5)(6)(7). Moreover, our group reported for the first time the feasibility and safety of a structured RAKT program from deceased donors (DDs) (4).…”

Section: Introductionmentioning

confidence: 98%

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The University of Florence Technique for Robot-Assisted Kidney Transplantation: 3-Year Experience

et al. 2020

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Objective: To report the University of Florence technique for robot-assisted kidney transplantation (RAKT) from living donor (LD) and deceased donor (DD), highlighting the evolution of surgical indications and technical nuances in light of a single surgeon's learning curve. Materials and Methods: A dedicated program for RAKT from LDs was developed at our Institution in 2017 and implemented later with a specific framework for DDs. All RAKTs were performed by a single highly experienced surgeon. Data from patients undergoing RAKT between January 2017 and December 2019 were prospectively collected in a dedicated web-based data platform. In this report we provide a comprehensive step-by-step overview of our technique for RAKT, focusing on the potential differences in peri-operative and mid-term functional outcomes between LDs vs. DDs. Results: Overall, 160 KTs were performed in our center during the study period. Of these, 39 (24%) were performed with a robot-assisted laparoscopic technique, both from LDs ( n = 18/39 [46%]) and from DDs ( n = 21/39 [54%]). Eleven (11/39 [18%]), 13(13/39 [26%]), and 15 (15/39 [30%]) RAKTs were performed in 2017, 2018, and 2019, respectively, highlighting an increasing adoption of robotics for KT over time at our Institution. Median time for arterial (19 min for LD and 18 min for DD groups), venous (21 min for LD, 20 min for DD) and uretero–vesical (18 min for LD and 15 for DD) anastomosis were comparable between the two groups (all p > 0.05), as the median rewarming time (59 min vs. 56 min, p = 0.4). The rate of postoperative surgical complications according to Clavien–Dindo classification did not differ between the two study groups, except for Clavien–Dindo grade II complications (higher among patients undergoing RAKT from DDs, 76 vs. 44%, p = 0.042). Overall, 7/39 (18%) patients (all recipients from DDs) experienced DGF; two of them were on dialysis at last FU. Conclusions: Our experience confirms the feasibility, safety, and favorable mid-term outcomes of RAKT from both LDs and DDs in appropriately selected recipients, highlighting the opportunity to tailor the technique to specific recipient- and/or graft-characteristics. Further research is needed to refine the technique for RAKT and to evaluate the benefits and harms of robotics for kidney transplantation from DDs.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Patient Positioning and Port Placementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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The University of Florence Technique for Robot-Assisted Kidney Transplantation: 3-Year Experience

et al. 2020

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“…8 A recent publication reported that a minimum of 35 RAKT cases are necessary to reach reproducibility in terms of renal rewarming time (RWT), complications, and functional results. 9 Ultimately, this steep learning curve may lead to lower graft and patient survival rates, which can hinder the integration and success of RAKT for recipients.…”

Section: Introductionmentioning

confidence: 99%

Development of a High-Fidelity Robot-Assisted Kidney Transplant Simulation Platform Using Three-Dimensional Printing and Hydrogel Casting Technologies

Saba

Belfast

Melnyk

et al. 2020

Journal of Endourology

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Introduction and Objective: Despite the adoption of robotic donor nephrectomy, the steep learning curve of robotic recipient transplantation has hindered the implementation of a complete robot-assisted kidney transplantation (RAKT). We sought to develop a high-fidelity perfused full immersion nonbiohazardous platform for RAKT simulation training. Methods: A three-dimensional (3D) computer-aided design (CAD) model consisting of a kidney, pelvicaliceal system, renal artery, and vein was created from a CT scan of a donor patient. 3D printed casts designed from the CAD model were injected with various polyvinyl alcohol hydrogel formulations to fabricate an anatomical kidney phantom and surrounding abdominal cavity. The process was repeated using a recipient's CT scan to create the recipient pelvic model containing a bony pelvis, pelvic musculature, iliac arteries and veins, and bladder. Donor and recipient models each contained structures to simulate the perfused vascular and ureterovesical anastomosis. A board-certified transplant surgeon completed a robotic training curriculum, including four RAKT simulation procedures, from procurement of the donor kidney to final retroperitonealization. Metrics from the simulations (e.g., arterial, venous, ureterovesical, and total anastomosis times) were recorded and compared with surgical times from published data. Results: The average time for the nephrectomies was 67.33 (-31.58) minutes. The average total anastomosis time was 60.85 (-9.73) minutes with 20.37 (-3.87), 20.17 (-4) and 15.1 (-2.35) minutes for arterial, venous, and ureterovesical anastomosis, respectively. The recorded arterial and venous anastomosis times were within published times for competency (D = 2.47 and D = 2.87, respectively), whereas the uterovesical time was within the mastery range (D = 0.45). Conclusions: Using a combination of 3D printing and hydrogel casting technologies, a high fidelity perfused full-immersion nonbiohazardous simulation platform for RAKT was developed. The utilization of this platform has the potential to replace the early cases in a learning curve while decreasing the barriers to utilization for transitioning transplant surgeons.

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Robotic Renal Transplantation

Diana

Gallioli

Decaestecker

et al. 2022

Robotic Urologic Surgery

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Learning Curve in Robot-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group

Cited by 64 publications

References 22 publications

The University of Florence Technique for Robot-Assisted Kidney Transplantation: 3-Year Experience

The University of Florence Technique for Robot-Assisted Kidney Transplantation: 3-Year Experience

Development of a High-Fidelity Robot-Assisted Kidney Transplant Simulation Platform Using Three-Dimensional Printing and Hydrogel Casting Technologies

Robotic Renal Transplantation

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