Analysis of the medication rules of famous traditional Chinese medicine practitioners for the treatment of Idiopathic Membranous Nephropathy based on data mining

Corresponding author: chenqin, chenqin2858@163.com

DOI: 10.12201/bmr.202507.00050

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  Abstract: Abstract Objective To explore the medication patterns of nationally renowned veteran Traditional Chinese Medicine (TCM) practitioners in treating challenging aspects of Idiopathic Membranous Nephropathy (IMN) based on data mining. Methods Medical records meeting the inclusion and exclusion criteria were collected. Statistical analysis of syndrome patterns, herb frequency, association rules, and cluster analysis were conducted for key challenges, including disease duration ≥1 year, renal impairment, hypoalbuminemia, and hypertriglyceridemia. Results A total of 128 medical cases were included. Spleen-kidney deficiency syndrome was identified as the most common pattern. Based on herb frequency and association rule analysis, Radix Astragali, Atractylodes macrocephala, Wolfiporia extensa, angelica sinensis and salvia miltiorrhiza were the most frequently used in prescription. Cluster analysis revealed core herbal groupings primarily based on classical formulas such as Zhenwu Decoction,Shenling Baizhu Powder, and Shuilu Erxian Dan. Conclusion In the medical cases addressing treatment challenges, the syndrome is characterized by root deficiency and branch excess, with the core therapeutic principle focusing on fortifying the spleen and tonifying the kidney. For patients with a disease duration ≥1 year, insect-derived herbs were added to dredge collaterals and dislodge the disease root. Cases with renal impairment emphasized warming yang and dispelling wind; those with hypoalbuminemia prioritized nourishing yin, consolidating the root, and clearing heat-toxins; and patients with hypertriglyceridemia were additionally treated with heat-clearing and dampness-resolving methods.

  Key words: idiopathic membranous nephropathy; difficulty in treatment; famous old Chinese medicine practitioners; medication rules; data mining

  Submit time: 16 July 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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