Application of improved glomerular filtration rate estimation by a neural network model in patients with neurogenic lower urinary tract dysfunction

Background: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (GFR) estimating equations - including the new Chronic Kidney Disease Epidemiology creatinine (CKD-EPIcr) equation without race and the estimated glomerular filtration rate (eGFR) equation developed for the Chinese population - displayed suboptimal performance in patients with neurogenic lower urinary tract dysfunction (NLUTD), which limited their clinical application for detecting changes in GFR levels in all cohorts. Objective: To develop a neural network model based on multilayer perceptron (MLP) for evaluating GFR in Chinese NLUTD patients, and compare the diagnostic performance with Cr-based multiple linear regression equations for Chinese and the CKD-EPIcr equation without race. Design: Single-center, cross-sectional study of GFR estimation from serum Cr, demographic data, and clinical characteristics in Chinese patients with NLUTD. Patients: A total of 204 NLUTD patients, from 27 different geographic regions of China, were selected. A random sample of 141 of these subjects was included in the training sample set, and the remaining 63 patients were included in the testing sample set. Methods: The reference GFR (rGFR) was assessed by the technetium-99m-labeled diethylenetriaminepentaacetic acid (99mTc-DTPA) double plasma sample method. A neural network model based on MLP was developed to evaluate GFR in the training sample set, which was then validated in the testing sample set and compared with Cr-based GFR equations. Results: The MLP-based model showed significant performance improvement in evaluating the difference, absolute difference, precision, and accuracy of GFR estimation compared with the Cr-based GFR equations. Additionally, compared with the rGFR, we found that the MLP-based model provided an acceptable level of accuracy (greater than 85%, which was within a 30% deviation from the rGFR). Conclusion: The MLP-based model offered significant advantages in estimating GFR in Chinese NLUTD patients, and its application could be suggested in clinical practice.