Surgical Refinement in Porcine Renal Autotransplantation - Flattening the Learning Curve in an Established Training Program.

J Surg Res

Department of Surgery and Transplantation, Faculty of Medicine, University Hospital RWTH Aachen, Aachen, Germany; Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany. Electronic address:

Published: August 2025


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Article Abstract

Introduction: Complex animal models, such as the porcine renal autotransplantation (pRaTx) model, provide an excellent platform for translational research. The pRaTx model is challenging, offering many possibilities to refine surgical procedures and optimize learning curves and outcomes. In this study, we described the critical initial steps toward flattening the learning curve in pRaTx.

Methods: We performed 51 consecutive cases of pRaTx in German landrace pigs divided between two teams, based on the experience level of the lead surgeon. Duration of all surgical steps, graft and recipient outcomes were monitored and specific pitfalls and possible refinement approaches were pointed out.

Results: Significant (P < 0.05) differences were observed between team-1/2 concerning warm-ischemia (28.0(24.0-34.5) versus 40.0(34.5-47.0) min) and anastomosis times (27.0(22.0-33.0) versus 38.0(33.0-44.0) min). Consequently, retention parameters were higher in the animals of team-2. Nevertheless, these differences did not manifest in "hard" clinical outcomes, such as vascular complications, survival. About 10 cases were required in both teams for a stable surgical performance.

Conclusions: As machine perfusion approaches and xenotransplantation are increasing in the spotlight of clinical interest, setting up a reliable and reproducible model for pRaTx is critical for translational research. As we could show, the pRaTx model requires an optimized team approach to refine the procedure.

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http://dx.doi.org/10.1016/j.jss.2025.05.013DOI Listing

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Introduction: Complex animal models, such as the porcine renal autotransplantation (pRaTx) model, provide an excellent platform for translational research. The pRaTx model is challenging, offering many possibilities to refine surgical procedures and optimize learning curves and outcomes. In this study, we described the critical initial steps toward flattening the learning curve in pRaTx.

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