Predicting estimated glomerular filtration rate after partial and radical nephrectomy based on split renal function...

Area of Science:

• Nephrology
• Urology
• Radiology

Background:

• Accurate prediction of postoperative estimated glomerular filtration rate (eGFR) is crucial for surgical decision-making in patients with complex renal masses.
• Choosing between radical nephrectomy (RN) and partial nephrectomy (PN) necessitates reliable forecasting of renal function post-procedure.
• Split glomerular filtration rate measured by radionuclide (rGFR) offers a potential basis for these predictions.

Purpose of the Study:

• To develop and validate predictive models for postoperative eGFR following RN and PN.
• To utilize preoperative split rGFR measurements as the primary predictor in these models.
• To aid in preoperative decision-making for surgical interventions on renal masses.

Main Methods:

• Retrospective analysis of patients who underwent RN or PN for a single renal mass between 2008 and 2022.
• Preoperative split rGFR assessed using technetium-99m-diethylenetriaminepentaacetic acid (Tc-99m DTPA) renal dynamic imaging.
• Linear mixed-effect models employed to predict short-term (<7 days) and long-term (3 months to 5 years) eGFRs; predictive ability quantified by marginal R-squared.

Main Results:

• Models were established for predicting long-term eGFR after RN (marginal R²=0.554) and PN (marginal R²=0.630).
• Models for predicting short-term eGFR after RN (marginal R²=0.692) and PN (marginal R²=0.656) were also developed.
• Laparoscopic and robotic surgery demonstrated superior outcomes for long-term eGFR compared to open surgery in both RN and PN.

Conclusions:

• Novel predictive tools for short-term and long-term eGFR after RN and PN have been successfully developed.
• These models, based on split rGFR, provide valuable quantitative insights for preoperative surgical planning.
• The findings support the use of these predictive tools to optimize patient management and surgical approach selection.