Exploring Traditional Chinese Medicine in Treating Gouty Arthritis: A Study of Drug Combination Patterns

Traditional Chinese Medicine (TCM) has been proved to have advantages on low-toxicity and can benefit decreasing uric acid for the treatment of gouty arthritis disease. However, there is a challenge to discover effective drug combinations from large amount drug usage due to complex drug variations in TCM prescriptions. To that end, this paper proposes a new weighted Apriori algorithm for association rule mining to discover drug combination patterns more accurately compared with conventional Apriori algorithm. In addition, this paper applies a Fast-Newman algorithm to explore and validate the usage patterns of TCM for the treatment of gouty arthritis through comparing a list of complex network algorithms. Experiment data is 315 actual outpatient medical records from the Guangdong Provincial Traditional Chinese Medicine Hospital, which is a top-ranked TCM hospital in China. According to the result by the weighted Apriori algorithm, the Chinese medicine Zexie and Tufuling are the most frequently used drug combination for the treatment of the disease. In the statistics of drug category, the medicinal properties are mainly cold, while the medicinal flavors are mainly bitter and sweet. According to the result by the Fast-Newman algorithm, four core communities of drug usage are identified, one of them suggesting that it is necessary to focus on the adverse emotions and sleep quality in the treatment of the disease. The experiment results provide therapeutic reference for clinical practice of TCM drug usage for the treatment of gouty arthritis disease.