Chinese Journal of Pharmacovigilance ›› 2024, Vol. 21 ›› Issue (5): 553-558.
DOI: 10.19803/j.1672-8629.20240030

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Analysis of prescription rules for Omphalia lapidescens based on the Dictionary of Chinese Traditional Medicine Prescriptions

LI Yao1,2, CHEN Yuxin1,2, GAO Haiyun1,2, LI Hui1,2, LIU Tianrui1,2,3#, YUAN Yuan1,2,4,5,*   

  1. 1Key Laboratory of Sustainable Utilization of Traditional Chinese Medicine Resources in Jiangxi Province, Institute of Traditional Chinese Medicine Health Industry, China Academy of Chinese Medical Sciences, Nanchang Jiangxi 330115, China;
    2Jiangxi Health Industry Institute of Traditional Chinese Medicine, Nanchang Jiangxi 330115, China;
    3Yunnan Key Laboratory of Gastrodia and Fungi Symbiotic Biology, Zhaotong University, Zhaotong Yunnan 657099, China;
    4State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica China Academy of Chinese Medical Sciences, Beijing 100700, China;
    5School of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining Qinghai 810007, China
  • Received:2024-01-12 Online:2024-05-15 Published:2024-05-13

Abstract: Objective To explore the prescription and medication rules of Omphalia lapidescens in the Dictionary of Chinese Traditional Medicine Prescriptions based on data mining method. Methods With the Dictionary of Chinese Traditional Medicine Prescriptions as the information source, the prescriptions containing O. lapidescens were identified, and a prescription database for O. lapidescens was created. The methods of enhancing the efficacy and reducing the toxicity of O. lapidescens, the types of symptoms and the compatibility of O. lapidescens were discussed by using literature data mining methods. The compatibility characteristics of O. lapidescens in common diseases were explored by association rule analysis. Pearson correlation analysis was used to uncover drug- disease correlations and summarize medication patterns. Results The main dosage forms of O. lapidescens prescription were pill and powder, the high frequency drugs were Areca catechu, Rheum officinale, and Aucklandia lappa. The compatibility of O. lapidescens was anthelmintics, purgatives, and drugs for regulating Qi flow with the flavors of bitter or spicy. Meridian tropism is mainly distributed in the spleen and stomach meridian. Among them, “A. catechu-O. lapidescens” had the highest frequency of drug pair compatibility, followed by “R. officinale-O. lapidescens”, and then “A. lappa-O. lapidescens”. The O. lapidescens formula has the highest frequency of treating the main condition of worm accumulation, followed by malnutrition and stagnation. The results of Pearson correlation analysis showed that the treatment of worm accumulation was compatible with A. catechu, A. lappa, Quisqualis indica, Ulmus macrocarpa, and Carpesium abrotano; Treatment malnutrition was compatible with picrorhiza scrophulariiflora, Coptis chinensis, and Citrus reticulata; Treatment malnutrition stagnation was compatible with Massa fermentata, Citrus reticulata, Pharbitis nil, and Sparganium stoloni. Conclusion The combination of O. lapidescens (Lei Wan) and A. catechu (Bing Lang) can enhance the efficacy of killing worms and eliminating stagnation; The combination of O. lapidescens (Lei Wan), P. scrophulariiflora (Hu Huanglian), and R. officinale (Da Huang) may increase the effect of diarrhea and attack the accumulation, which may cause mild gastrointestinal adverse reactions; The combination of O. lapidescens (Lei Wan), A. Citrus reticulata Blanco (Chen Pi) and M. Fermentata (Shen Qu) can protect gastric mucosa and reduce gastrointestinal adverse reactions. However, the basic research on the toxic substances of O. lapidescens has not been reported, and further research is still needed to provide a more accurate basis for the clinical use of O. lapidescens.

Key words: Omphalia lapidescens, Dictionary of Chinese Traditional Medicine Prescriptions, the compatibility of traditional Chinese medicine (TCM), prescription medication, literature data mining, association rules, Pearson correlation analysis

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