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Predicting GFR after radical nephrectomy: the importance of split renal function
- Source :
- World Journal of Urology. 40:1011-1018
- Publication Year :
- 2022
- Publisher :
- Springer Science and Business Media LLC, 2022.
-
Abstract
- To evaluate a conceptually simple model to predict new-baseline-glomerular-filtration-rate (NBGFR) after radical nephrectomy (RN) based on split-renal-function (SRF) and renal-functional-compensation (RFC), and to compare its predictive accuracy against a validated non-SRF-based model. RN should only be considered when the tumor has increased oncologic potential and/or when there is concern about perioperative morbidity with PN due to increased tumor complexity. In these circumstances, accurate prediction of NBGFR after RN can be important, with a threshold NBGFR 45 ml/min/1.73m236 RCC patients who underwent RN (2010-2012) with preoperative imaging (CT/MRI) and relevant functional data were included. NBGFR was defined as GFR 3-12 months post-RN. SRF was determined using semi-automated software that provides differential parenchymal-volume-analysis (PVA) from preoperative imaging. Our SRF-based model was: Predicted NBGFR = 1.24 (× Global GFRThe correlation-coefficients (r) were 0.87/0.72 for SRF-based/non-SRF-based models, respectively (p = 0.005). For prediction of NBGFR 45 ml/min/1.73mPrevious non-SRF-based models to predict NBGFR post-RN are complex and omit two important parameters: SRF and RFC. Our proposed model prioritizes these parameters and provides a conceptually simple, accurate, and clinically implementable approach to predict NBGFR post-RN. SRF can be easily obtained using PVA software that is affordable, readily available (FUJIFILM-Medical-Systems), and more accurate than nuclear-renal-scans. The SRF-based model demonstrates greater predictive-accuracy than a non-SRF-based model, including the clinically-important predictive-threshold of NBGFR 45 ml/min/1.73m
Details
- ISSN :
- 14338726
- Volume :
- 40
- Database :
- OpenAIRE
- Journal :
- World Journal of Urology
- Accession number :
- edsair.doi.dedup.....49f099c8ad532f70d3514e6a567255f6
- Full Text :
- https://doi.org/10.1007/s00345-021-03918-9