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. 2025 Jun;45(3):676-684.
doi: 10.19852/j.cnki.jtcm.2025.03.002.

A prognostic model of immunoglobulin A nephropathy using artificial neural network: a retrospective study based on integrated Chinese and Western Medicine

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A prognostic model of immunoglobulin A nephropathy using artificial neural network: a retrospective study based on integrated Chinese and Western Medicine

Chen Hongyu et al. J Tradit Chin Med. 2025 Jun.

Abstract

Objective: To establish and evaluate a prognostic model of immunoglobulin A nephropathy (IgAN) based on integrated Chinese and Western Medicine.

Methods: Retrospective analysis from 1/1/2013 to 12/31/2015 was performed on 735 patients who were diagnosed with IgAN. In addition, 105 external data sets from 1/1/2016 to 12/31/2018 were used to verify the constructed model. The end point was entry into end-stage renal disease or a doubling of serum creatinine (Scr) level from baseline. Kaplan-Meier curve survival analysis and multivariable Cox regression analysis were used to find independent prognostic factors. MATLAB 2018b and artificial neural network (ANN) were used to construct prognostic risk factor prediction models each for Traditional Chinese Medicine (TCM), Western Medicine, and integrated TCM and Western Medicine. The ANN model incorporated WANG Yongjun's new five-type syndrome differentiation for IgAN. The prediction efficiencies of the three models were compared using the confusion matrix and the area under thecurve (AUC).

Results: Patients from 1/1/2013 to 12/31/2015 were followed for a mean of (46 ± 19) months. The 5-year median overall renal survival time was 58.6 months, and a total of 40 patients (5.4%) entered the endpoint. Ratio of males to females was 1.48:1. Median age of patients undergoing renal puncture was 35 years. Median 24-hour urinary protein was 0.55 g and 37 patients (5.0%) had pronounced proteinuria (24-hour urine protein ≥ 3.5 g). Median serum creatinine was 76 μmol/L and mean estimated glomerular filtration rate was (90 ± 33) mL/min per 1.73 m2. Oxford classification of renal pathology suggested a high rate of focal segmental glomeru-losclerosis (80.3%). Use of immunosuppressants was the most common (71.3%) treatment after renal puncture and improved clinical outcomes of IgAN. TCM differentiation of kidney deficiency was the most common syndrome (69.5%). Independent risk factors for the endpoint were male, anemia, high urinary protein, and an Oxford classification of segmental sclerosis (S). AUCs of the Western Medicine, TCM, and integrated Chinese and Western Medicine models were 0.89, 0.87, and 0.92, respectively. In external data (1/1/2016 to 12/31/2018), the performance of the three models was 0.88, 0.80, and 0.94, respectively.

Conclusions: ANN can be used to successfully construct a 5-year prediction model of IgAN after renal puncture. The efficiency of this model, which combines TCM and Western Medicine factors based on Wang's new five-type syndrome differentiation, exceeds that of Western Medicine factors or TCM factors alone in data from this single-center retrospective study.

Keywords: Medicine, Chinese TraditionalSupporting information; convolutional neural networks; glomerulonephritis, IGA; prognosis.

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Figures

Figure 1
Figure 1. Enrollment of patients
eGFR: estimated glomerular filtration rate; IgAN: immunoglobulin A nephropathy.
Figure 2
Figure 2. Results of K-M survival curve of laboratory variables that were statistically different (P < 0.05)
A: sex (female = 0, male = 1); B: anemia (without anemia = 0, anemia = 1); C: hyperuricemia (non-hyperuricemia = 0, hyperuricemia = 1); D: hypercholesterolemia (non-hypercholesterolemia = 0, hypercholesterolemia = 1); E: high-LDL (non-high-density lipoprotein = 0, high-density lipoprotein = 1); F: 24-h urinary protein quantitation (24-h urinary protein quantitation ≤ 1 g = 0, 24-h urinary protein quantitation > 1 g = 1); G: Scr (normal range Scr = 0, elevated Scr = 1); H: eGFR (eGFR ≥ 90 mL/min per 1.73 m2 = 0, eGFR < 90 mL/min per 1.73 m2 = 1). K-M: Kaplan-Meier; LDL: low density lipoprotein; eGFR: estimated glomerular filtration rate.
Figure 3
Figure 3. Results of K-M survival curve of renal pathology variables, treatment regimen, and Wang’s new five-type syndrome differentiation that were statistically different (P < 0.05)
A: Oxford classification of S (segmental sclerosis) (S = 0 or 1); B: Oxford classification of T (interstitial fibrosis/tubular atrophy) (T = 0 or 1 or 2); C: immunosuppressive agents (without immunosuppressive agents = 0, with immunosuppressant = 1); D: kidney deficiency syndrome (without kidney deficiency syndrome = 0; with kidney deficiency syndrome = 1); E: wind-dampness syndrome (without wind-dampness syndrome = 0; with wind-dampness syndrome = 1); F: uremic syndrome (without uremic syndrome = 0, with uremic syndrome = 1).

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References

    1. Rodrigues JC, Haas M, Reich HN. IgA nephropathy. Clin J Am Soc Nephrol 2017; 12: 677-86. - PMC - PubMed
    1. Kamano C, Shimizu A, Joh K, et al. A cross-sectional study in patients with IgA nephropathy of correlations between clinical data and pathological findings at the time of renal biopsy: a Japanese prospective cohort study. Clin Exp Nephrol 2021; 25: 509-21. - PubMed
    1. Barbour SJ, Espino-Hernandez G, Reich HN, et al. The MEST score provides earlier risk prediction in IgA nephropathy. Kidney Int 2016; 89: 167-75. - PubMed
    1. Barbour SJ, Cattran DC, Kim SJ, et al. Individuals of Pacific Asian origin with IgA nephropathy have an increased risk of progression to end-stage renal disease. Kidney Int 2013; 84: 1017-24. - PubMed
    1. Ganzer PD, Loeian MS, Roof SR, et al. Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine. Sci Adv 2022; 8: eabj5473. - PMC - PubMed

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