Study on medication regularity of traditional Chinese medicine cases in treatment of neoplastic fever based on data mining

• 作者: Ya-fang Cai Fei-Yu Xie Yun Mao Peng-Yuan Jiang Xue-Lei Chu Peng Xue Shi-Jie Zhu
• 来源期刊: 海南医科大学学报（英文版）
• 年，卷（期）: 2021,（24）
• 所属期刊栏目: Original article
• 页码范围: 55-60
• 页数: 6页
• 语种: 英文

摘要

Objective: To analyze the medication regularity of traditional Chinese medicine cases in treatment of neoplastic fever in order to guide clinical medication. Methods: The database of China National Knowledge Infrastructure,Vip database and WanFang medical network were searched.The cases involving traditional Chinese medicine prescription in the treatment of neoplastic fever were screened.After extracting the prescriptions and Chinese medicines,make statistics according to frequency analysis,cluster analysis and association analysis. Results: 79 literatures were included which involving 123 decoctions.221 traditionalChinese medicines were included in the statistics, the most frequently used traditional Chinese medicines were Gancao,Chaihu,Huangqi and Shengdihuang. The proportion of heat-clearing drugs in Chinese medicines was the largest(23.98％).The most common property of the Chinese medicines is cold property,accounting for 51.13％.The higher frequencies of flavors of the Chinese medicines are bitter,sweet and acrid,the sum of which is 84.66％.The most common meridian of Chinese medicines is liver meridian,accounting for 19.82％.The cluster analysis and association analysis of high frequency Chinese medicines showed that high frequency Chinese medicines could form three clustering formulas,and could get 18 pairs of high frequency drug combinations. Conclusion: Traditional Chinese medicines for heat-clearing,deficiency-tonifying,phlegm-resolving,blood stasis-dispeling are mostly used to the treatment of neoplastic fever.The results of cluster analysis and association analysis of high frequency traditional Chinese medicines can provide certain reference and guidance for clinical medication.