ArticleWorld journal of urology2022
Predicting GFR after radical nephrectomy: the importance of split renal function.
Article in World journal of urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 35 citations in OpenAlex.
- Preoperative prediction of preserved renal parenchymal volume via multilevel CT feature fusion: a proof-of-concept study.Abdominal radiology (New York) · 2026Article
- Multimodal deep learning model for AI-based functional prognostic risk stratification in patients undergoing radical nephrectomy.Nature communications · 2026Article
- Is it Always Safe to Administer RAS Inhibitors to Patients Who Underwent Unilateral Radical Nephrectomy?Case reports in nephrology · 2026Article
- Developing a CT radiomics-based model for assessing split renal function using machine learning.Japanese journal of radiology · 2025Article
- Impact of tumor size and sex on diagnostic discrepancies in renal mass imaging.Scientific reports · 2025Article
- AI-based automatic estimation of single-kidney glomerular filtration rate and split renal function using non-contrast CT.Insights into imaging · 2025Article
- Renal parenchymal volume analysis: Clinical and research applications.BJUI compass · 2025Review
- Cumulative Impact of Serial Partial Nephrectomy for the Treatment of Recurrent Renal Masses.The Journal of urology · 2024Article
- Practical Prediction of New Baseline Renal Function After Partial Nephrectomy.Annals of surgical oncology · 2024Article
- Predicting new-baseline glomerular filtration rate (NBGFR) after donor nephrectomy: validation of a split renal function (SRF)-based formula.World journal of urology · 2024Article
- Choosing the larger kidney on CT volumetry: a study on the early post-donation kidney function of living donors.International urology and nephrology · 2024Article
- Predicting estimated glomerular filtration rate after partial and radical nephrectomy based on split renal function measured by radionuclide: a large-scale retrospective study.World journal of urology · 2023Article
- Preoperative Renal Parenchyma Volume as a Predictor of Kidney Function Following Nephrectomy of Complex Renal Masses.European urology open science · 2023Article
- New-onset Chronic Kidney Disease After Surgery for Localised Renal Masses in Patients with Two Kidneys and Preserved Renal Function: A Contemporary Multicentre Study.European urology open science · 2023Article
- Point of care parenchymal volume analyses to estimate split renal function and predict functional outcomes after radical nephrectomy.Scientific reports · 2023Article
- Optimizing prediction of new-baseline glomerular filtration rate after radical nephrectomy: are algorithms really necessary?International urology and nephrology · 2022Article
- Split Renal Function Is Fundamentally Important for Predicting Functional Recovery After Radical Nephrectomy.European urology open science · 2022Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo 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/1.73m
methods236 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 GFR
resultsThe 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/1.73m
conclusionPrevious 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
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