The Development of a Predictive Model for Postoperative Renal Function in Living Kidney-Transplant Donors

建立活体肾移植供体术后肾功能预测模型

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Abstract

Background/Objectives: The accurate prediction of postoperative renal function (post-RF) in living kidney donors is essential for optimizing donor safety and long-term health. After nephrectomy, renal function can be significantly altered, owing to the functional adaptation of the remaining kidney; however, the extent of this has not been investigated. This study aimed to examine how various donor factors affect functional adaptation after nephrectomy, and to develop a new predictive model. Methods: In total, 310 patients who underwent donor nephrectomy were included. Preoperative split renal function (pre-SRF) of the remaining kidney was measured. Post-RF was measured 1 month after surgery. The functional adaptation rate was calculated from the difference between pre-SRF and post-RF. Multiple regression analysis was performed to develop a predictive formula for post-RF, incorporating donor age and pre-SRF. Results: The median age of the donors was 60 years, and 38.7% were men. The median pre-SRF was 36.4 mL/min/1.73 m(2). The median functional adaptation rate was 26.8%, with donor age, pre-SRF, and a history of hyperuricemia (HUA) being significant predictors of the functional adaptation rate. The equation for post-RF was established as 0.94 × pre-SRF - 0.12 × age + 18.87 mL/min/1.73 m(2). The estimated post-RF showed a high coefficient of determination (R(2) = 0.76), with a mean bias of -0.01 mL/min/1.73 m(2). Conclusions: Donor age, pre-SRF, and HUA are key predictors of renal functional adaptation after nephrectomy. The developed formula accurately estimates post-RF, supporting clinical decision-making and donor counseling for living kidney donations.

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