Abstract

To explore the etiology, pathogenesis, distribution of syndromes and the rule of medication of chronic atrophic gastritis(CAG) in Beijing-Tianjin-Hebei region based on the latent structure model. Chronic atrophic gastritis of 279 cases in Beijing-Tianjin-Hebei region were extracted from the established database of spleen and stomach diseases of famous veteran Chinese medicine experts. The latent structure models of symptoms and drugs of chronic atrophic gastritis were constructed by using Lantern 3.1.2 software, and the latent structure models were interpreted. SAS 10.0 software was used to mine association rules of drugs and symptoms. The constitutional characteristics of patients with chronic atrophic gastritis in Beijing-Tianjin-Hebei region were "turbid toxin and damaging Yin". The common syndromes were turbid toxin, deficiency of stomach Yin, stagnation of liver and stomach, stagnation of liver and stomach Qi, obstruction of stomach collaterals and blood stasis, and weakness of spleen and stomach. Common medicines are Lobeliae Chinensis Herba, Scutellariae Barbatae Herba, Amomi Fructus Rotundus, Amomi Fructus, Poria, Isatidis Radix, Artemisiae Scopariae Herba, Scorpio, Coptidis Rhizoma, Lilii Bulbus, Linderae Radix, Phragmitis Rhizoma, Ophiopogonis Radix, Pogostemonis Herba, Eupatorii Herba, Magnoliae Officinalis Cortex, Aurantii Fructus Immaturus. Common prescriptions are Baihe Wuyao Powder, Danggui Shaoyao Powder, Xiaoyao Pills, Xiangsu Powder, Dachengqi Decoction, Zuojin Pills, Qingzhong Decoction, Zhishi Daozhi Pills, etc. The application of latent structure model and correlation analysis in the empirical study of famous and veteran Chinese medicine experts is in line with the research direction of modern Chinese medicine "traditional Chinese medicine + X". The conclusions obtained effectively tap the experience of famous and veteran TCM experts, and provide a data and visual clinical reference and prescription compatibility for young TCM physicians in the treatment of chronic atrophic gastritis based on syndrome differentiation.

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