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Objective:To explore the prescription and medication law of Traditional Chinese Medicine (TCM) compounds in the treatment of vascular dementia (VD) based on patent database.Methods:TCM compounds with patents about VD were retrieved from Chinese patent announcement website of the State Intellectual Property Office and CNKI. The retrieval time was from the establishment to the databases to 31 st, March 2022. The frequency, clusteringand association analysis were carried out with the help of TCM inheritance auxiliary platform (V2.5). The medication law was analyzed. Results:154 TCM compound patents for the treatment of vascular dementia were screened, involving 227 kinds of Chinese materia medica. Among them, Acori Tatarinowii Rhizoma (44 times, 28.57%) was used more frequently, and the common medicinal pair was Salviea Miltiorrhizae Radix et Rhizoma- Acori Tatarinowii Rhizoma (17 times, 11.03%). The medicinal property was mainly warm, the taste was mainly sweet, and the meridian was mainly liver meridian. Those with high confidence based on association rules were " Corni Fructus -Acori Tatarinowii Rhizoma" (0.90), " Corni Fructus -Rehmannize Radix et Praeparata" (0.90). Based on the complex network, it was concluded that the core drugs were 14 groups such as " Rehmannize Radix et Praeparata- Cistanches Herba- Corni Fructus". The new prescriptions extracted by entropy cluster analysis included 7 groups such as " Rehmannize Radix et Praeparata, Cistanches Herba, Corni Fructus and Asparagi Radix". Conclusion:The treatment of VD by TCM compounds with national patents is mainly based on tonifying deficiency, promoting blood circulation and removing blood stasis, eliminating phlegm and dampness, expelling wind and dredging collaterals, opening orifices and resuscitation, which can provide reference for clinical practice and new drug research and development.
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Objective:To explore the macroscopic medication rule of Chinese medicine for the treatment of primary liver cancer and provide references for clinical medication. Method:The databases of CNKI，VIP， and Wanfang Data were searched for research articles published from September 1959 to June 2019 with the terms of "Chinese medicine" and "liver cancer". A database was established based on the collected Chinese medicinal prescriptions for the treatment of primary liver cancer. The frequency，clustering， and association rules were analyzed by Excel， etc. Result:In this study，106 effective articles were included，and after the modified prescriptions were removed， 92 effective prescriptions were screened out，involving 281 Chinese herbal medicines used for 1 181 times in total. The top 5 high-frequency drugs were Poria （deficiency-tonifying），Astragali Radix （heat-clearing），Bupleuri Radix （blood-activating and stasis-resolving），Paeoniae Radix Alba （urination-promoting and dampness-draining）， and Codonopsis Radix （Qi-regulating）. The analysis of drug flavor with a frequency higher than 10 showed that most of the drugs were sweet，bitter， and pungent in flavor，cold，warm， and plain in nature，and acted on spleen and liver meridians. Four combinations and 10 herbal pairs were obtained by the cluster analysis of high-frequency drugs and association analysis， respectively. The high-frequency drugs and potential herbal pairs were classified targeting the specific clinical syndromes in different stages of liver cancer. Conclusion:Replenishing Qi， invigorating spleen，clearing heat， removing toxin，activating blood， and resolving stasis were the basic principles for the treatment of primary liver cancer. The combination of those drugs was the main therapeutic strategy. In addition，the resulting 10 potential herbal pairs from high-frequency drugs and cluster analysis could inspire the clinical treatment of primary liver cancer in different clinical stages with various clinical syndromes， which was of reference value for the clinical medication.
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Objective:To analyze the data of Chinese medicine prescriptions for the treatment of coronavirus disease 2019 (COVID-19) in Shijiazhuang City, Hebei Province, with a view to further guide the clinical use of Chinese medicine in the prevention and treatment of COVID-19.Methods:Forty-eight patients diagnosed with COVID-19 who were treated by critical care team of Hebei Traditional Chinese Medicine Hospital in the intensive care unit (ICU) of Hebei Chest Hospital (Hebei Provincial COVID-19 designated hospital) from January 7 to March 4, 2021, were enrolled in this study. The patients' gender, age, clinical classification, past history, and all Chinese medicine prescriptions for the first visit and follow-up visits during the hospitalization were collected. A database was established based on the Ancient and Modern Medical Records Cloud Platform (V2.2.1), and the methods of frequency analysis, correlation analysis, cluster analysis, and complex network analysis were used to analyze the prescriptions of traditional Chinese medicine.Results:Among the 48 patients with COVID-19, 20 were males and 28 were females; the average age was (62.4±13.7) years old. The patients' condition was generally severe, including 17 cases of common type, 25 cases of severe type, and 6 cases of critical type, most of whom were combined with hypertension, coronary heart disease, diabetes, chronic obstructive pulmonary disease and other basic illnesses. A total of 146 valid prescriptions were included, involving 59 prescriptions and 115 Chinese medicines. Frequency analysis of 146 prescriptions showed that the commonly used prescriptions for patients with COVID-19 were Qingfei Paidu decoction (30 times, 20.55%), Xuanbai Chengqi decoction (10 times, 6.85%), and Dayuan Yin (10 times, 6.85%). The common Chinese medicines were liquorice (80 times, 54.79%), tuckahoe (76 times, 52.05%), gypsum (70 times, 47.95%), bitter almond (70 times, 47.95%), ephedra (57 times, 39.04%), scutellaria (56 times, 38.36%), tangerine peel (53 times, 36.30%), patchouli (50 times, 34.25%), atractylodes macrocephala (50 times, 34.25%), and bupleurum (43 times, 29.45%). The main effects were clearing heat and detoxification (129 times), clearing heat-fire (129 times) and eliminating dampness and diuresis (110 times). The medicinal properties were mainly warm (509 times), flat (287 times), and cold (235 times). The medicinal tastes were mainly pungent (765 times), sweet (654 times), and bitter (626 times). The medicinal channel tropism were mainly lung (1 096 times), spleen (785 times), and stomach (687 times). The correlation analysis showed that there were 17 drug combinations in total, among which the top 3 drug pairs in support were bitter almond-gypsum (0.43), ephedra-bitter almond (0.38), tangerine peel-poria (0.36), and ephedra-gypsum (0.36). Cluster analysis showed that there were 3 groups of clustering formulas. The first group was ephedra, bitter almond, and gypsum. The second group was patchouli, tuckahoe, tangerine peel, and atractylodes macrocephala. The third group was scutellaria, licorice, immature orange fruit, oriental waterplantain rhizome, bupleurum, ginger, and cassia twig. The core drugs were composed of tuckahoe, bupleurum, tangerine peel, atractylodes macrocephala, patchouli, bitter almond, scutellaria, gypsum, ephedra, and licorice.Conclusions:Middle-aged and elderly patients with COVID-19 are accompanied by Qi deficiency and internal invasion of toxins, and the pathogenesis evolves rapidly. Damp and turbid toxins often block the lungs and trap the spleen, leading to disorder of Qi movement, and even invaginate Ying and Xue, drain Yin and Yang. The treatment is based on removing turbidity and detoxification, and replenishing Qi and nourishing Yin are the principle treatments, so that the evil is eliminated and the Qi is restored.
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To explore the regularity of traditional Chinese patent medicines for the treatment of hyperlipidemia recorded in Newly Edited National Chinese Traditional Patent Medicines,the Composition Principles of Chinese Patent Drugs,New Drug Conversion Standard,the Compilation of National Standard for Traditional Chinese Medicines and Chinese Pharmacopoeia. Researchers extracted the information of prescriptions from these cases according to the inclusion and exclusion criteria. Then microsoft excel 2010 was used to conduct frequency statistics and count the frequency of traditional Chinese medicine. SPSS Clementine( ver.12. 0) and SPSS( ver. 18. 0)were adopted respectively for frequency analysis,association rules analysis,cluster analysis and factor analysis. Besides,KMO test and Bartlett spherical test were performed for factor adaptation test. Finally,a total of 173 traditional Chinese medicines were included,involving 94 Chinese patent medicine prescriptions. The frequency results of traditional Chinese medicine showed that there were 33 kinds of high-frequency traditional Chinese medicine,mainly including those for tonifying medicine,activating blood and resolving stasis and blood-stasis,and clearing damp. The association rules analysis found out 12 association rules of drug pairs,3-herb pairs of 25 and4-herb pairs of 6. Totally 11 medicine groups with relevance were respectively extracted by cluster analysis. KMO test and Bartlett spherical test indicated that the method was suitable for factor analysis and 11 common factors were respectively extracted by factor analysis. The association rules reflected the therapeutic method for tonify the liver and kidney,activating blood and resolving stasis. Cluster analysis and factor analysis showed the therapeutic method of Qi-enriching and Yin-nourishing,and the factor analysis focused more on removing blood stasis and dampness. The decision tree with hawthorn as the dependent variable reflects the importance of alisma orientalis and fructus schisandrae in the drug matching. In conclusion,data mining technique can comprehensively analyze the regularity of prescriptions of traditional Chinese patent medicine for hyperlipidemia,and is helpful for guiding the development of Chinese patent medicines and the clinical practice of traditional Chinese medicine.
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Humans , Drug Prescriptions , Drugs, Chinese Herbal , Hyperlipidemias , Medicine, Chinese Traditional , Nonprescription DrugsABSTRACT
Objective:To summarize medication law of prescription and clinical experience on the treatment of chronic cough through data mining technology. Method:The formula information of 650 cases of chronic cough cases diagnosed and treated by professor HAN Ming-xiang was processed with data mining technology, and system cluster analysis and factor analysis were conducted by SPSS Statistics 22.0. Result:High-frequency medicines of professor HAN Ming-xiang for treating chronic cough were Stemonae Radix, Citri Reticulatae Pericarpium, Asteris Radix et Rhizoma and other 37 herbs, their frequency of occurrence accounted for 80.52%. According to the efficacy, the medicines could be classified into 10 categories, such as expectorant cough antiasthmatic drugs, tonifying deficiency drugs, and diaphoretic drugs. Cluster analysis showed 5 combinations of drugs. Factor analysis yielded 13 common factors, such as Stemonae Radix-Asteris Radix et Rhizoma-Farfarae Flos-Cynanchi Stauntonii Rhizoma et Radix, Asari Radix et Rhizoma-Schisandrae Chinensis Fructus-Zingiberis Rhizoma-Fritillariae Thunbergii Bulbus. Conclusion:Combined with clinical experience, it can be concluded that clinical treatment of professor HAN Ming-xiang for chronic cough attaches great importance to the pathogenesis of wind-evil, Yang deficiency and cold phlegm underlying lung, phlegm and blood stasis and Qi stagnation. The treatment mainly starts from the lung and spleen, with the method of warm and moist, or with some traditional Chinese medicines with the function of removing phlegm by warming the lung, dispersing cold by thinning the surface, strengthening the spleen and resolving phlegm, strengthening the lung and fixing the surface, and relieving spasmolysis by wind.
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This paper was aimed to study medication laws of traditional Chinese medicine (TCM) towards rheumatoid arthritis (RA) based on modern medicine literatures. The China National Knowledge Infrastructure (CNKI), Wanfang Data knowledge service platform and VIP Database for Chinese Technical Periodicals were searched from January 2000 to December 2016 for relevant literatures on TCM for treatment of RA. The results showed that the database was established and the data were analyzed with statistics method including frequency analysis and cluster analysis. Finally, a total of 292 articles, 214 kinds of herbs were included, with a total frequency of 5071 for herbs. The results of frequency analysis, showed that tonic drugs, medicine for eliminating wind and dampness, drug for invigorating blood circulation and eliminating stasis were the main medications, followed by heat-cleaning drug, relieving external syndrome drug, and dampness-draining drug. The most common tastes of high frequency were sweet, pungent and bitter. The most common natures were warm and mild. The related meridians included the liver meridian, spleen meridian and kidney meridian. It was concluded that the cluster analysis showed medicines in the core group were as following: Astragalus, Licorice, Chinese angelica, Monkshood, Cassia twig, Coix seed, Radix saposhnikoviae, Radix gentianae macrophyllae, Notopterygium, Caulis spatholobi, Rhizoma ligustici wallichii, Twotooth achyranthes root, and Radix clematidis. The common combinations of RA drugs were summarized by association analysis. The medication law of RA treatment is to enrich consumptive disease and support healthy energy, to tonify the liver and kidney, to dispel wind and eliminate dampness, to remove blood stasis and dredge collaterals.
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Objective To analyze clinical differential diagnostics and medication law of CAI Lian-xiang of treating gynecological diseases from theChong-Ren;To provide references for clinical medication. Methods Medical cases of gynecological diseases treated by differential diagnostics from“Chong-Ren”from December 2013 to January 2015 in out-patient department of Xiyuan Hospital of CACMS by CAI Lian-xiang were collected. Excel2007 was used to establish the database, and the frequency and correlation analysis were made on the differentiation, treatment principles, treatment methods, medicine and medical combination by using the large data intelligent analysis system of Chinese medicine diagnosis and treatment. The results were confirmed with CAI Lian-xiang's academic thought and clinical experience. Results Totally 103 medical cases, 277 diagnosis times, 277 prescriptions and 92 kinds of Chinese materiamedica were included. Although different types of gynecological diseases from theChong-Ren treatment of specific treatment were different, all were related to liver, spleen and kidney;prescription contained 22 high-frequency medicines (>50 times), and the first three medicines were Cuscutae Semen 178 times (64.3%), Angelicae Sinensis Radix 167 times (60.3%), Paeonize Radix 158 times (57.0%). The association analysis results showed 9 combination of Tiaochongren medicine combination group, 11 Qiangchongren meidcine combination group, 4 Zichongren medicine combination group, and 4 Guchuanrenmediicne combination group. Conclusion CAI Lian-xiang believes that gynecological diseases are closely related to “Chong-Ren”, and treatment from“Chong-Ren”focuses on the adjustment and nourishment of liver, spleen and kidney. The data miningresults of medication law is accordance with the relevant academic thoughts, which can provide references for clinic.