Data Mining‐Based Analysis of Chinese Medicinal Herb Formulae in Chronic Kidney Disease Treatment

Abstract

Background. Traditional Chinese medicine (TCM) has long been used to treat chronic kidney disease (CKD) in Asia. Its effectiveness and safety for CKD treatment have been confirmed in documented studies. However, the prescription rule of formulae for Chinese medicinal herbs is complicated and remains uncharacterized. Thus, we used data mining technology to evaluate the treatment principle and coprescription pattern of these formulae in CKD TCM treatment. Methods. Data on patients with CKD were obtained from the outpatient system of a TCM hospital. We established a Chinese herb knowledge base based on the Chinese Pharmacopoeia and the Chinese Materia Medica. Then, following extraction of prescription information, we deweighted and standardized each prescribed herb according to the knowledge base to establish a database of CKD treatment formulae. We analyzed the frequency with which individual herbs were prescribed, as well as their properties, tastes, meridian tropisms, and categories. Then, we evaluated coprescription patterns and assessed medication rules by performing association rule learning, cluster analysis, and complex network analysis. Results. We retrospectively analyzed 299 prescriptions of 166 patients with CKD receiving TCM treatment. The most frequently prescribed core herbs for CKD treatment were Rhizoma Dioscoreae (Shanyao), Spreading Hedyotis Herb (Baihuasheshecao), Root of Snow of June (Baimagu), Radix Astragali (Huangqi), Poria (Fulin), Rhizoma Atractylodis Macrocephalae (Baizhu), Radix Pseudostellariae (Taizishen), and Fructus Corni (Shanzhuyu). The TCM properties of the herbs were mainly being warm, mild, and cold. The tastes of the herbs were mainly sweet, followed by bitter. The main meridian tropisms were Spleen Meridian of Foot-Taiyin, Liver Meridian of Foot-Jueyi, Lung Meridian of Hand-Taiyin, Stomach Meridian of Foot-Yangming, and Kidney Meridian of Foot-Shaoyin. The top three categories were deficiency-tonifying, heat-clearing, and dampness-draining diuretic. Conclusion. Using an integrated analysis method, we confirmed that the primary TCM pathogeneses of kidney disease were deficiency and dampness-heat. The primary treatment principles were tonifying deficiency and eliminating dampness-heat.

Identifying Compound Effect of Drugs on Rheumatoid Arthritis Treatment Based on the Association Rule and a Random Walking-Based Model

“…In the clustering analysis algorithm, each herb was regarded as a cluster, and N clusters were combined to form a new class based on the similarity between objects. The Euclidean metric was used to calculate similarity between herbs [ 14 ]: …”

“…Each drug was treated as a variable in this dataset. The formulae [ 14 ] applied were as follows: where X ⟶ Y is an association rule, X (left-hand side (LHS)) and Y (right-hand side (RHS)) represent the set of herb items, σ ( X ) is the frequency of itemset X , X ∪ Y is the union of itemsets X and Y , σ ( X ∪ Y ) is the frequency with which itemsets X and Y appear together, support( X ⟶ Y ) is the frequency with which X and Y appear together, and confidence( X ⟶ Y ) is the probability that itemset Y appears in the presence of X . Expected confidence( X ⟶ Y ) is the probability that itemset Y appears without any conditional influence.…”

Traditional Chinese Medicine Could Play an Important Role in Integrative Palliative Care in China

“…[2][3][4][5][6][7][8][9][10][11] Qigong can also improve cognitive function in the early stages of dementia, 12 whereas TCM decoctions can be used as adjuvant treatment for patients with stroke and chronic obstructive pulmonary disease, chronic liver disease, chronic heart failure, and chronic or type 2 diabetic kidney disease. [13][14][15][16][17][18][19][20][21][22][23][24][25][26] Second, TCM can improve symptoms. For example, acupuncture and Chinese herbal medicines are recommended for cancer pain and serve to reduce opioid abuse.…”

FangNet: Mining herb hidden knowledge from TCM clinical effective formulas using structure network algorithm

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