Development and validation of multilayer perceptual neural network in glomerular filtration rate evaluation
10.3760/cma.j.cn441217-20210825-00054
- VernacularTitle:基于多层感知神经网络的肾小球滤过率评估模型的开发和验证
- Author:
Yang XIE
1
;
Yingchun MA
;
Jigang YANG
;
Yali NIE
;
Zhenbo CHEN
;
Chunli ZHANG
;
Li ZUO
Author Information
1. 首都医科大学康复医学院 中国康复研究中心北京博爱医院影像科，北京 100068
- Keywords:
Glomerular filtration rate;
Neural networks (Computer);
Renal insufficiency, chronic
- From:
Chinese Journal of Nephrology
2022;38(5):369-378
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop a neural network model for the evaluation of glomerular filtration rate (GFR) based on multilayer perceptual neural network, and to compare with the improved Chinese based creatinine GFR evaluation formula (C-GFR cr) and the evaluation formula (EPI-GFR cr) of the American Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) for the clinical applicability of multilayer perceptual neural network model in evaluating GFR. Methods:A total of 684 chronic kidney disease (CKD) patients used for developing a modified version of China′s based creatinine GFR evaluation formula were taken as the research object. The data of 454 patients were randomly selected as the development group and the data of the other 230 patients were as the verification group. The multilayer perceptual neural network GFR evaluation model (M-GFR cr) was established. With the double plasma GFR as the reference value (rGFR), the correlation, mean difference, mean absolute difference, precision and accuracy of C-GFR cr, EPI-GFR cr and M-GFR cr were compared. Results:Among the 684 CKD patients, there were 352 males and 332 females, with age of (49.9±15.8) years. The correlation between M-GFR cr and rGFR was the highest (Pearson correlation =0.93, P<0.001). The mean difference of M-GFR cr was lower than that of C-GFR cr ( Z=9.929, P<0.001) and EPI-GFR cr ( Z=10.573, P<0.001). The mean absolute difference of M-GFR cr was also lower than that of C-GFR cr ( Z=3.953, P<0.001) and EPI-GFR cr ( Z=4.210, P<0.001). The accuracy of ±15% of M-GFR cr was higher than that of C-GFR cr ( χ2=26.068, P<0.001) and EPI-GFR cr ( χ2=23.154, P<0.001). The accuracy of ±30% of M-GFR cr was also higher than that of C-GFR cr ( χ2=8.264, P=0.001) and EPI-GFR cr ( χ2=11.963, P=0.001). The results of different stages of CKD showed that in the early stage of CKD (CKD 1-2), the mean difference of M-GFR cr was lower than that of C-GFR cr ( Z=7.401, P<0.001) and EPI-GFR cr ( Z=8.096, P<0.001); the mean absolute difference of M-GFR cr was also lower than that of C-GFR cr ( Z=4.723, P<0.001) and EPI-GFR cr ( Z=4.946, P<0.001); the accuracy of ±15% of M-GFR cr was higher than that of C-GFR cr ( χ2=23.547, P<0.001) and EPI-GFR cr ( χ2=26.421, P<0.001); the accuracy of ±30% of M-GFR cr was also higher than that of C-GFR cr ( χ2=12.089, P=0.001) and EPI-GFR cr ( χ2=16.168, P<0.001). But there was no significant difference in the applicability among C-GFR cr, EPI-GFR cr and M-GFR cr in the advanced stages of CKD (CKD 3-5). Conclusion:Compared with the improved Chinese based creatinine GFR evaluation formula C-GFR cr and CKD-EPI evaluation formula EPI-GFR cr, the accuracy of multilayer perceptual neural network model to evaluate GFR in CKD patients has been significantly improved, especially in CKD 1-2 stage.
