Predicting estimated glomerular filtration rate after partial and radical nephrectomy based on split renal function measured by radionuclide: a large-scale retrospective study

Author:

Zheng Wanxiang,Hou Guangdong,Ju Dongen,Yan Fei,Liu Kepu,Niu Zhiping,Huang Luguang,Xing Zibao,Kong Lingchen,Liu Pengfei,Zhang Geng,Wei Di,Yuan JianlinORCID

Abstract

Abstract Purpose The purpose of this study was to develop predictive models for postoperative estimated glomerular filtration rate (eGFR) based on the split glomerular filtration rate measured by radionuclide (rGFR), as choosing radical nephrectomy (RN) or partial nephrectomy (PN) for complex renal masses requires accurate prediction of postoperative eGFR. Methods Patients who underwent RN or PN for a single renal mass at Xijing Hospital between 2008 and 2022 were retrospectively included. Preoperative split rGFR was evaluated using technetium-99 m-diethylenetriaminepentaacetic acid (Tc-99 m DTPA) renal dynamic imaging, and the postoperative short-term (< 7 days) and long-term (3 months to 5 years) eGFRs were assessed. Linear mixed-effect models were used to predict eGFRs, with marginal R2 reflecting predictive ability. Results After excluding patients with missing follow-up eGFRs, the data of 2251 (RN: 1286, PN: 965) and 2447 (RN: 1417, PN: 1030) patients were respectively included in the long-term and short-term models. Two models were established to predict long-term eGFRs after RN (marginal R2 = 0.554) and PN (marginal R2 = 0.630), respectively. Two other models were established to predict short-term eGFRs after RN (marginal R2 = 0.692) and PN (marginal R2 = 0.656), respectively. In terms of long-term eGFRs, laparoscopic and robotic surgery were superior to open surgery in both PN and RN. Conclusions We developed novel tools for predicting short-term and long-term eGFRs after RN and PN based on split rGFR that can help in preoperative decision-making.

Funder

Key Research and Development Projects of Shaanxi Province

Publisher

Springer Science and Business Media LLC

Subject

Urology

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