Rules Of Traditional Chinese Medicine Research Articles

Analysis of medication rule of Traditional Chinese Medicine in treating depression based on data mining

ObjectiveDepression is a mental disorder characterized by persistent feelings of sadness, decreased interest or pleasure in activities and reduced energy. As a highly prevalent disorder, it seriously endangers the psychosocial functioning of patients. Many scholars have conducted clinical studies on the treatment of depression using different herbal remedies, but there are no studies that integrate these remedies to explore the general medication rule. This study aims to explore the medication pattern of Traditional Chinese Medicine (TCM) treatment for depression through data mining methods, so as to provide scientific theoretical basis and reference for clinical treatment and new prescription development. MethodsBased on the PRISMA principle, 121 articles involving 10810 patients with depression of TCM treatment were collected. We then performed frequency, association rule, and hierarchical clustering analysis of Chinese herbs using Microsoft Excel 2016, SPSS Modeler 18.0 and IBM SPSS Statistics 23. ResultsAmong the 270 herbs collected, the three most frequently occurring herbs are Gancao, Chaihu, and Shaoyao. The categories of high-frequency herbs are mainly deficiency-tonifying, Qi-regulating and blood-activating and stasis-eliminating herbs. Through the Apriori algorithm, we mined 21 herbal groups of association rules, and among which the combination of Chaihu-Shaoyao-Gancao has the highest level of support. Furthermore, five novel clustering combinations were identified, predominantly derived from Xiaoyao-San, Chaihu-Shugan-San, Sini powder, Kaixin-San and Chaihu-Jia-Longgu-Muli Decoction. ConclusionThe current study not only concluded the frequent combinations but also developed five new drug cluster combinations for depression, which can provide evidence-based references for the future clinical treatment and is helpful to understand the potential pharmaceutical mechanism from the properties, tastes, meridian tropisms and categories. The clinical effectiveness of these combinations needs to be verified by future study.

Medication rules of Chinese herbs in treatment of H-type hypertension based on data mining

Based on the R language data mining technology, the medication rules of traditional Chinese medicine(TCM) in the treatment of H-type hypertension were discussed, and the basis and new ideas for the treatment of H-type hypertension with TCM were provided. CNKI, Wanfang, VIP, and SinoMed were searched to collect clinical studies on the treatment of H-type hypertension with TCM. The data were screened, and Excel was used to build a database. Rstudio was used to carry out drug efficacy classification, four Qi and five flavors, meridian homing, frequency of use, correlation, association rules, and clustering analyses of drugs and explore the medication rules of TCM. 191 TCM prescriptions were obtained, and the main syndromes were phlegm-dampness accumulation syndrome, phlegm and blood stasis syndrome, and Yin deficiency and Yang hyperactivity syndrome. A total of 169 kinds of TCM were used, and the frequency was 1 875 times. Among them, the drugs whose single use frequency was more than 20 times were high-frequency medicines, 26 kinds in total. They were Gestrodiae Rhizoma, Poria, Pinelliae Rhizoma, Achyranthis Bidenthis Radix, Glycyrrhizae Radix et Rhizoma, etc. The efficacy of high-frequency medicines was mainly classified as tonic medicines, blood-activating and stasis-removing medicines, liver-relieving wind medicines, and damp-clearing medicines. The four Qi of the drug were mainly warm and flat, and the five flavors were mainly sweet and bitter. The liver meridian and spleen meridian were the main meridians. The association rule analysis obtained a total of 14 groups of commonly used drug combinations, and the correlation analysis obtained 20 drug combinations with a high correlation coefficient. A total of six drug combinations were obtained by cluster analysis. Eight groups of drug pairs were obtained by association rule analysis on H-type hypertension with phlegm-dampness accumulation syndrome. Seven drug combinations with high correlation coefficients were obtained by correlation analysis, and three drug prescriptions were obtained by cluster analysis. The pathological factors of H-type hypertension are mainly phlegm, stasis, and deficiency. The disease site is in the liver, involving the spleen, lungs, and other viscera. The commonly used drugs are Gestrodiae Rhizoma, Poria, Pinelliae Rhizoma, Achyranthis Bidenthis Radix, etc. Banxia Baizhu Tianma Decoction, Tianma Gouteng Decoction, and Buyang Huanwu Decoction are commonly used prescriptions. The medication rules shown in this study can provide certain ideas for the clinical treatment of H-type hypertension with TCM.

Study on the Medication Rules of Traditional Chinese Medicine for Acne Treated from Lung Based on Data Mining

Study on the Medication Rules of Traditional Chinese Medicine for Acne Treated from Lung Based on Data Mining

Exploring the Prescription Rules of Traditional Chinese Medicine for Treating Chronic Prostatitis Based on Data Mining

Exploring the Prescription Rules of Traditional Chinese Medicine for Treating Chronic Prostatitis Based on Data Mining

Medication rule of traditional Chinese medicine in the treatment of plateau hypoxia based on data mining.

The development of traditional Chinese medicine (TCM) in the plateau area is relatively backward. There is a lack of system to analyze the effects of the special environment of plateau low pressure and hypoxia on human meridians qi and blood, as well as the etiology and pathogenesis of plateau hypoxic diseases. To analyze the composition rules of anti-hypoxia TCM formulation with data mining methods. The experimental literatures related to high altitude hypoxia were searched in China National Knowledge Infrastructure (CNKI), Wanfang Med Online, VIP, China Biology Medicine disc and other databases, a standardized prescription database was established after screening and standardization of prescription data in the literature. The composition rules of these prescription including drug frequency, drug attributes, drug efficacy, drug combination, and core prescription were analyzed and displayed with visual charts. A total of 135 TCM prescriptions were included, and 229 flavored drugs were included. Among these prescriptions, the TCM with high frequency of use were Astragalus, Danshen, Ginseng, and Angelica, etc. Four natures of the TCM were mostly warm and calm. Five flavours of the TCM were mostly sweet, bitter, and pungent. And channel tropism of the TCM mostly entered the heart, lung, and liver meridians. The frequency combination of TCM was Astragalus-Danshen and Astragalus-Angelica. The core medicines of these prescriptions were Astragalus, Danshen, Angelica, Rhodiola, Goji, and Ginseng. TCM could alleviate symptoms such as chest tightness, chest pain, coughing and wheezing, coughing, vomiting, fatigue, and loss of appetite caused by hypoxia at high altitude. Through data mining, it is concluded that the prevention or treatment of plateau hypoxic diseases mostly utilized products can nourish blood, replenish qi and dispel stasis, and help yang and dispel qi, most of them are compatible with qi tonic drugs and blood circulation and stasis dissolving drugs, and pay attention to the combination of virtual and real, yin and yang.

Prescription and medication rules of traditional Chinese medicine for prevention and treatment of diabetic microangiopathy based on literature mining

This study explored the prescription and medication rules of traditional Chinese medicine(TCM) in the prevention and treatment of diabetic microangiopathy based on literature mining. Relevant literature on TCM against diabetic microangiopathy was searched and prescriptions were collected. Microsoft Excel 2021 software was used to establish a prescription database, and an analysis was conducted on the frequency, properties, flavors, meridian tropism, and efficacy classifications of drugs. Association rule analysis, cluster analysis, and factor analysis were performed using SPSS Modeler 18.0 and SPSS Statistics 26.0 software. The characteristic active components and mechanisms of action of medium-high frequency drugs in the analysis of medication rules were explored through li-terature mining. A total of 1 327 prescriptions were included in this study, involving 411 drugs, with a total frequency reaching 19 154 times. The top five high-frequency drugs were Astragali Radix, Angelicae Sinensis Radix, Poria, Salviae Miltiorrhizae Radix et Rhizoma, and Rehmanniae Radix. The cold and warm drugs were used in combination. Drugs were mainly sweet, followed by bitter and pungent, and acted on the liver meridian. The majority of drugs were effective in tonifying deficiency, clearing heat, activating blood, and resolving stasis. Association rule analysis identified the highly supported drug pair of Astragali Radix-Angelicae Sinensis Radix and the highly confident drug combination of Poria-Alismatis Rhizoma-Corni Fructus. The strongest correlation was found among Astragali Radix, Angelicae Sinensis Radix, Poria, and Salviae Miltiorrhizae Radix et Rhizoma through the complex network analysis. Cluster analysis identified nine categories of drug combinations, while factor analysis identified 16 common factors. The analysis of active components in high-frequency drugs for the treatment of diabetic microangiopathy revealed that these effective components mainly exerted their effects by inhibiting oxidative stress and suppressing inflammatory reactions. The study found that the pathogenesis of diabetic microangiopathy was primarily characterized by deficiency in origin, with a combination of deficiency and excess. Deficiency was manifested as Qi deficiency and blood deficiency, while excess as phlegm-heat and blood stasis. The key organ involved in the pathological changes was the liver. The treatment mainly focused on supplementing Qi and nourishing blood, supplemented by clearing heat, coo-ling blood, activating blood, and dredging collaterals. Commonly used formulas included Danggui Buxue Decoction, Liuwei Dihuang Pills, Erzhi Pills, and Buyang Huanwu Decoction. The mechanisms of action of high-frequency drugs in the treatment of diabetic microangiopathy were often related to the inhibition of oxidative stress and suppression of inflammatory reactions. These findings can provide references for the clinical treatment of diabetic microangiopathy and the development of targeted drugs.

An Analysis of the Clinical Medication Rules of Traditional Chinese Medicine for Polycystic Ovary Syndrome Based on Data Mining.

The aim of the present study is to investigate the rules and characteristics of the clinical administration of traditional Chinese medicine (TCM) in the treatment of polycystic ovary syndrome (PCOS) using data mining methods. Medical cases of well-known contemporary TCM doctors treating PCOS were collected from the China National Knowledge Infrastructure, Chinese Biomedical Literature Service System, Wanfang, Chinese Scientific Journals Database, and PubMed; the data were then characterized, and a standardized database of medical cases was built. This database was used to (1) count the frequency of syndrome types and the herbs used in medical cases by data mining methods and (2) analyze drug association rules and systematic clustering methods. A total of 330 papers were included, involving 382 patients and a total of 1,427 consultations. The most common syndrome type was kidney deficiency; sputum stasis was the core pathological product and causative factor. A total of 364 herbs were used. Among them, 22 herbs were used >300 times, including Danggui (Angelicae Sinensis Radix), Tusizi (Semen Cuscutae), Fuling (Poria), Xiangfu (Nutgrass Galingale Rhizome), and Baizhu (Atractylodis Macrocephalae Rhizoma). Additionally, 22 binomial associations were obtained from the analysis of association rules; five clustering formulae were obtained via the analysis of high-frequency drug clusters; and 27 core combinations were obtained by k-means clustering of formula. In the treatment of PCOS, TCM is primarily employed as a combination approach involving tonifying the kidneys, strengthening the spleen, eliminating damp and dissolving phlegm, activating blood circulation, and resolving blood stasis. The core prescription is primarily a compound intervention based on the Cangfu Daotan pill, Liuwei Dihuang pill, and Taohong Siwu decoction.

Retracted: Analysis of Prescription Medication Rules of Traditional Chinese Medicine for Diabetes Treatment Based on Data Mining.

[This retracts the article DOI: 10.1155/2022/7653765.].

Analysis of prescription medication rules of traditional Chinese medicine for bradyarrhythmia treatment based on data mining.

Multiple studies have revealed that Traditional Chinese Medicine (TCM) prescriptions can provide protective effect on the cardiovascular system, increase the heart rate and relieve the symptoms of patients with bradyarrhythmia. In China, the TCM treatment of bradyarrhythmia is very common, which is also an effective complementary therapy. In order to further understand the application of Chinese medicines in bradyarrhythmia, we analyzed the medication rules of TCM prescriptions for bradyarrhythmia by data mining methods based on previous clinical studies. We searched studies reporting the clinical effect of TCM on bradyarrhythmia in the PubMed and Chinese databases China National Knowledge Infrastructure database, and estimated publication bias by risk of bias tools ROB 2. Descriptive analysis, hierarchical clustering analysis and association rule analysis based on Apriori algorithm were carried out by Microsoft Excel, SPSS Modeler, SPSS Statistics and Rstidio, respectively. Association rules, co-occurrence and clustering among Chinese medicines were found. A total of 48 studies were included in our study. Among the total 99 kinds of Chinese medicines, 22 high-frequency herbs were included. Four new prescriptions were obtained by hierarchical cluster analysis. 81 association rules were found based on association rule analysis, and a core prescription was intuitively based on the grouping matrix of the top 15 association rules (based on confidence level), of which Guizhi, Zhigancao, Wuweizi, Chuanxiong, Danshen, Danggui, Huangqi, Maidong, Dangshen, Rougui were the most strongly correlated herbs and in the core position. In this study, data mining strategy was applied to explore the TCM prescription for the treatment of bradyarrhythmia, and high-frequency herbs and core prescription were found. The core prescription was in line with the treatment ideas of TCM for bradyarrhythmia, which could intervene the disease from different aspects and adjust the patient's Qi, blood, Yin and Yang, so as to achieve the purpose of treatment.

Study on Medication Rules of Traditional Chinese Medicine in Treating Constipation through Data Mining and Network Pharmacology.

Background To explore the rules of TCM medication in the treatment of constipation in network pharmacology. Methods Collect and screen the clinical intervention literature on TCM for constipation from China's national knowledge infrastructure, Wanfang and VIP databases established a database of TCM for constipation, applied R software (3.3.1) to analyze the pattern of prescriptions for TCM for constipation, and summarized the core prescription. The effective active compounds and action targets in the core prescription were screened by Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Traditional Chinese Medicine Integrated Databases (TCMID), constipation-related targets were derived from the DisGeNET and GeneCards databases, Protein-protein interaction network (PPI) was drawn by STRING database, and enrichment analysis was conducted by the Clusterprofiler package in R software (3.3.1). Finally, molecular docking was used to validate the binding ability of candidate compounds to potential targets. Results Two hundred sixteen target prescriptions were screened through data mining, involving 226 herbs. Association rule analysis results suggested that the “Angelicae sinensis-Radix-dried rehmanniae-Cistanche deserticola-Atractylodes macrocephala-Astragali Radix” was a strong affinity for medicine. Network pharmacology analysis of the core prescription resulted in the screening of 115 candidate compounds, such as quercetin, kaempferol, mangostin, eugenol A, and beta-sitosterol; 131 potential targets, such as PTGS2, PTGS1, and CHRM3; and 160 signaling pathways, such as lipid and atherosclerosis, proteoglycans in cancer, hepatitis B, Kaposi's sarcoma-associated herpesvirus infection, and PI3K/AKT pathways. Molecular docking showed that PTGS1-formononetin, PTGS2-kaempferol, and CHRM3-kaempferol were all well bound and well matched. Conclusions This study provides a new method and ideas for clinical applications of integrated Chinese and western medicine in treating constipation.

Medication rule of traditional Chinese medicine for heart failure after myocardial infarction: based on data mining

This study aims to explore the medication rule of traditional Chinese medicine(TCM) for heart failure after myocardial infarction via data mining. To be specific, articles on the treatment of the disease with Chinese medicine were retrieved from CNKI, Wanfang, VIP, and SinoMed and related information was collected. A database was created with Microsoft Excel 2019, and SPSS Clementine 12.0 and IBM SPSS Statistics 23.0 were applied for association rules analysis, cluster analysis, and factor analysis. Finally, a total of 81 TCM prescriptions were screened out, involving 91 medicinals with cumulative use frequency of 740. The main syndromes were Qi deficiency and blood stasis, Yang Qi deficiency and blood stasis together with retained morbid fluid, deficiency of both Qi and Yin and blood stasis. The medicinals with high-frequency were Astragali Radix, Salviae Miltiorrhizae Radix et Rhizoma, Ginseng Radix et Rhizoma, Poria, and Aconiti Lateralis Radix Praeparata. The effects of the medicinals were tonifying deficiency, activating blood and resolving stasis, and promoting urination and draining dampness. The association rules analysis yielded "Astragali Radix-Salviae Miltiorrhizae Radix et Rhizoma" "Astragali Radix-Aconiti Lateralis Radix Praeparata-Salviae Miltiorrhizae Radix et Rhizoma" "Aconiti Lateralis Radix Praeparata-Ginseng Radix et Rhizoma-Salviae Miltiorrhizae Radix et Rhizoma-Astragali Radix" combinations. Cluster analysis yielded 6 basic formulas for heart failure after myocardial infarction. Factor analysis extracted a total of 8 common factors. Heart failure after myocardial infarction is characterized by the syndrome of deficiency in nature and excess in superficiality. The core pathogenesis is "deficiency" "stasis" "retained morbid fluid", particularly "deficiency". This disease is closely related to the heart, lung, and spleen. The basic treatment principle is replenishing Qi and activating blood, and warming Yang, excreting water, and nourishing yin should also be emphasized. The common basic prescriptions, such as Siwu Decoction, Shengmai Powder, Xuefu Zhuyu Decoction, Linggui Zhugan Decoction, and Shenfu Decoction, have been discovered. This study provided data for clinical medication and drug development for heart failure after myocardial infarction.

Medication Regularity of Traditional Chinese Medicine in the Treatment of Aplastic Anemia Based on Data Mining.

Aplastic anemia (AA) is an uncommon disease, characterized by pancytopenia and hypocellular bone marrow, but it is common in the blood system. The medication rules of traditional Chinese medicine (TCM) in the treatment of AA are not clear, for which it is worth exploring the medication rules by data mining methods. This study used SPSS Modeler 18.0 and SPSS statistics to analyze the cases of AA from Zhejiang Provincial Hospital of Chinese Medicine (ZJHCM) from March 1, 2019, to March 1, 2022. Data mining methods, including frequency analysis, cluster analysis, and association rule learning, were performed in order to explore the medication rules for AA. (1) A total of 859 prescriptions, which met the inclusion criteria, consisted of 255 herbs. In descending order of the frequency of herbal medicine, we have Danggui, Huangqi, Shudihuang, Fuling, Gancao, Shanyao, Shanzhuyu, Baizhu, Dangshen, and Xianhecao. (2) Frequency analysis of herb properties: the Four Qi of 255 kinds of TCMs are mainly warm and neutral medicines. The Five Flavors are mainly sweet medicines, followed by bitter medicines. The main meridians are the liver, spleen, and kidney. (3) Clustering of medications: TCMs with the top 20 frequencies are classified into 9 groups by cluster analysis. (4) Association rule analysis of high-frequency herbs: using the Apriori algorithm, the results showed that there were 3 herb pairs with support of over 0.3 and 12 herb pairs with confidence above 0.85. The basic pathogenesis of AA (Sui Lao) is spleen and kidney essence deficiency, Qi deficiency, and blood stasis. The main herbs have warm and neutral properties, sweet tastes, and liver, spleen, and kidney meridian tropisms, whose purpose is to tonify the kidney and invigorate the spleen, tonify Qi, and promote blood circulation.

Network Pharmacology and Data Mining Approach Reveal the Medication Rule of Traditional Chinese Medicine in the Treatment of Premenstrual Syndrome/Premenstrual Dysphoric Disorder.

Premenstrual syndrome (PMS) is a common disorder that affects women of reproductive age. It is characterized by periodic mental and somatic symptoms such as irritability, depression, and breast pain during the luteal phase. Premenstrual dysphoric disorder (PMDD) is the most severe form of PMS. In recent years, the incidence of PMS/PMDD has been increasing year after year. However, due to the complex symptoms and ambiguous classification of PMS/PMDD, the limitations of present treatments, such as their poor efficacy rate, have become increasingly apparent. With its unique benefits such as syndrome differentiation and high cure rate, traditional Chinese medicine (TCM) has sparked new diagnosing and treating of PMS/PMDD. This study uses data mining methods, and statistical analysis revealed that Xiaoyao San and Chaihu Shugan San were the commonly used TCM to treat PMS/PMDD. A detailed investigation of regularly used single herbs revealed that most TCM is used as cold herbs that penetrate the liver meridian, with predominant bitter, sweet, and pungent flavors. The network pharmacology method analyzes the interactions between diseases, targets, and herbs. Meanwhile, the deep action targets and molecular mechanisms of 10 commonly used herbs for the treatment of PMS/PMDD are studied, revealing that it involves several ingredients, many targets, and different pathways. This interaction provides insight into the mechanism of action of TCM in the synergistic treatment of PMS/PMDD. It is now clear that we can begin treating PMS/PMDD with TCM using the target and mechanism revealed by the abovementioned findings in the future. This serves as an essential reference for future research and clinical application of TCM in the treatment of PMS/PMDD.

Patent information analysis of TCM prescription for the treatment of diabetes based on patent analysis and SWOT model

ObjectiveTo analyze the patent information and medication rules of traditional Chinese medicine (TCM) prescriptions for the treatment of diabetes, so as to provide reference for domestic pharmaceutical enterprises in new drug development and patent layout. MethodsThe retrieval strategy was formulated based on the characteristics of TCM prescription. The patent data were retrieved by incoPat and WTMPD patent database. SPSS Statistic21.0 was used to analyze the internal strengths (S), weaknesses (W), opportunities (O) and threats (T) of TCM for the treatment of diabetes on the basis of patent analysis, and different types of combinations of strategies were worked out. ResultsAt present, the patent application for the prescription of TCM for the treatment of diabetes gradually enters the declining period. Three typical domestic pharmaceutical companies (Hebei Yiling Pharmaceutical, Tianjin Tianshili Pharmaceutical and Lunan Pharmaceutical Group) have their own characteristics in the field of technological innovation and patent layout in the treatment of diabetes, but there is a defect of insufficient power of original technology. The high-frequency core TCM for the treatment of diabetes is Radix Astragali, Angelica sinensis, Salvia miltiorrhiza, Chinese yam, Pueraria lobata and so on. The taste of the medicine is mainly sweet, the medicine is warm and flat, and most of them return to the spleen and liver meridian. The prescription of TCM for the treatment of diabetes should be based on replenishing qi and nourishing yin, clearing heat and promoting fluid. ConclusionThe development of TCM patents related to diabetes in China should take the opportunity of market demand and domestic policy support, draw lessons from the characteristic system of TCM patents of key patentees, pay attention to the layout of the peripheral patents and international kindred patents, and establish patent early warning and navigation analysis system at home and abroad to effectively reduce the risk of patent infringement in the international environment.

Analysis on the medication rule of traditional Chinese medicine in the treatment of COVID-19 patients.

Objective:To describe patterns of utilization of traditional Chinese medicine (TCM) in the treatment of patients with coronavirus disease 2019 (COVID-19).Methods:Adult patients with COVID-19 who received TCM treatment were divided into a non-serious group (mild and moderate types) and a serious group (severe and critical types) according to their admission conditions. The medical records and prescriptions of these patients were investigated to determine their TCM utilization patterns.Results:In all, 3,872 COVID-19 patients were included. Oral Chinese traditional patent medicine (CPM) was the most commonly used type of TCM, followed by decoction. The proportion of multi-drug combinations was higher than single drug use (55.0% vs. 45.0%). Decoction combined with oral CPM was the most common combination (39.1%, 1,514/3,872). Orally administered, injected, and externally applied CPM were significantly more common in the serious group than in the non-serious, while decoction and non-drug TCM treatments were more common in the non-serious than in the serious group. Multi-drug combinations were used for the majority of patients in both groups, mainly in the form of decoctions combined with oral CPM. Among the serious patients, injected CPM was more often used in patients who died during treatment (35.0%, 36/103). The two most common medication patterns were decoction combined with oral CPM and oral CPM alone in the two finally discharged groups. Oral CPM alone or used in combination with injected CPM were seen most commonly in the death group. Significant differences were established in TCM utilization and medication patterns among patients in three groups who had different prognoses and outcomes.Conclusions:The treatment measures and medication patterns of TCM commonly used in COVID-19 patients with the range of conditions found in this study should be further explored in the future to provide a more complete reference for COVID-19 treatment.

Analysis of prescription and medication rules of traditional Chinese medicine in the treatment of the coronavirus disease 2019 based on traditional Chinese medicine inheritance support platform

To analyze the rules of medication and principles of formulas for the treatment of coronavirus disease 2019 (COVID-19) using the traditional Chinese medicine inheritance support platform (V2.5). The clinical data, including gender, age, clinical symptoms, frequency of traditional Chinese medicine medication and prescription information, of patients with COVID-19 and asymptomatic infection who were admitted to Hebei COVID-19 designated hospital supported by medical team of First Affiliated Hospital of Hebei University of Chinese Medicine from January to March 2021 were collected. The information data were input into the traditional Chinese medicine inheritance support platform (V2.5). The data mining and analysis were realized by the integrated association rules and complex entropy clustering analysis methods of the software, including the analysis of the frequency of each drug use, drug meridian, taste, and prescription rules, and the new prescriptions were developed. A total of 564 patients (564 prescriptions) were enrolled, involving 200 Chinese herbs, including 357 cases of common COVID-19 and 207 cases of asymptomatic infection. The proportion of women with common COVID-19 was high, and the high incidence age group was 51-70 years old. There was no significant difference in gender of asymptomatic infection, and the high incidence age group was 1-20 years old. The main clinical manifestations of most patients were head heavy and cough, followed by low fever and cough with sputum, the main tongue coating and pulse pattern were similar in both types of patients. The frequency of traditional Chinese medicine used in patients with common type of COVID-19 from high to low was liquorice root (326 times), indian bread (264 times), pinellia tuber (263 times), bitter apricot seed (236 times), baical skullcap root (229 times), gypsum (205 times), agastache rugosus (201 times), dried tangerine peel (194 times), ephedra (184 times), and Chinese thorowax root (163 times), while that used by asymptomatic infection were baical skullcap root (174 times), liquorice root (142 times), medicated leaven (137 times), agastache rugosus (127 times), pinellia tuber (114 times), Chinese thorowax root (100 times), officinal magnolia bark (91 times), atractylodes rhizome (89 times), peony root (84 times), and milkvetch root (83 times). The two types of patients were mainly treated with warm, cold and flat drugs, and the nature and taste were mainly pungent, bitter and sweet. The meridian tropism of drugs was mainly lung, spleen and stomach. High frequency drug formulation mainly included drugs for resolving turbidity and detoxification. At the same time, seven new prescriptions for common COVID-19 and four new prescriptions for asymptomatic infection were developed. The primary reason for the COVID-19 occurrence and development is turbidity-toxin and the qi of plague, and resolving turbidity and detoxication are the basic treating principle. On the basis, for patients with common COVID-19, symptomatic treatment such as relieving exterior syndrome, clearing heat, resolving phlegm, and antitussive drugs should be taken into account at the same time, while the treatment of asymptomatic infections should focus more on supporting the body and eliminating the harmful pathogens.

Analysis of Prescription Medication Rules of Traditional Chinese Medicine for Diabetes Treatment Based on Data Mining.

In this study, we have used TCM medical record management platform and SAS statistical software to analyze the cases of a professor in the treatment of type 2 diabetes, in order to explore the medication rules for the treatment of type 2 diabetes, so as to enrich and optimize the diagnosis and treatment plan for type 2 diabetes based on the experience of famous doctors. Chinese medicine treatment provides more diagnosis and treatment ideas. We have collected the professor's treatment of type 2 diabetes, screened out 100 patients, from a total of 285 prescriptions, and entered them into the TCM medical record management platform. We used the TCM medical record management platform and SAS statistical software to analyze his professor's experience in the treatment of type 2 diabetes. The medication analysis is as follows: (1) frequency of medication: 285 cases that met the inclusion criteria used a total of 187 traditional Chinese medicines. Among them, Salvia miltiorrhiza was used most frequently; (2) drug frequency analysis: 285 cases met the inclusion criteria, and the four Qi were mainly cold and warm medicines. The five flavors are mainly sweet, bitter, and pungent drugs. The main meridians are the liver, spleen, and kidney; (3) drug efficacy and classification analysis: 285 cases met the inclusion criteria, and 285 cases met the inclusion criteria and the Chinese medicines involved are the most common medicines used for tonic, heat clearing, blood circulation, and stasis; (4) clustering of medications: 35 Chinese medicines with medication frequency ≥20% are divided into 11 categories. (5) Using the improved Apriori algorithm, the minimum confidence level is selected to be 0.5, data mining is conducted on all type 2 diabetes cases, and a total of 21 recipes are dug out involving 10 Chinese medicines. In this study, with the aid of the TCM medical record management platform and SAS statistical software, cluster analysis, improved Apriori algorithm, and other data mining methods were used to systematically and objectively analyze the professor's treatment of type 2 diabetes cases. The results have clinical significance and can be used for traditional Chinese medicine treatment of type 2 diabetes, which provides an objective basis and provides a certain reference for the current inheritance of traditional Chinese medical experience and summary research.

Analysis on Medication Rules of Traditional Chinese Medicine for Postpartum Abdominal Pain

Analysis on Medication Rules of Traditional Chinese Medicine for Postpartum Abdominal Pain

Study on Medication Rules of Traditional Chinese Medicine Against Inflammatory Breast Cancer Based on Bioinformatics and Network Pharmacology

Study on Medication Rules of Traditional Chinese Medicine Against Inflammatory Breast Cancer Based on Bioinformatics and Network Pharmacology

Analysis on oral medication rules of traditional Chinese medicine prescriptions for prevention of COVID-19

ObjectiveTo analyze the medication rules of traditional Chinese medicine (TCM) preventive oral prescriptions for COVID-19. MethodsThe preventive oral prescriptions for COVID-19 published by national and provincial health and wellness committees, administrations of TCM, medical institutions at all levels, medical masters and Chinese medicine experts were collected to establish a database, manual screening was carried out according to the inclusion and exclusion criteria, and frequency statistics, association rule analysis. The mutual information method, entropy hierarchical clustering and other methods were improved through Excel and the TCM inheritance auxiliary platform V2.5 to mine the rules and characteristics of medication. ResultsThe selected 157 prescriptions contained a total of 130 TCMs. The top five TCMs with the highest use frequency were Glycyrrhizae Radix et Rhizoma (86), Astragali Radix (80), Lonicerea Japonicae Flos (70), Atractylodis Macrocephalae Rhizoma (62), Saposhnikoviae Radix (60). In accordance with TCM efficacy classification, most of them were medicines for qi-tonifying (279), followed by medicines for clearing heat and drying dampness (163), dispelling pathogenic wind-cold (126), resolving dampness (111), as well as dispelling pathogenic wind-heat (99). The characteristics of four-natures of the selected medicines are as follows: most of them were cold (59), followed by warm (38) and mild (21). In terms of five-taste, most of them were sweet (26) and acrid-and-bitter (24), followed by sweet-and-bitter (20), bitter (20) and acrid (15). For the meridian attribution, the five-zang organs and six-fu organs were all involved, most of them attributed to lung meridian (80), followed by stomach meridian (57) and spleen meridian (40). Based on association rule analysis, 12 commonly used medicine combinations with two or three TCMs were found. The commonly used medicinal pairs included Astragali Radix and Saposhnikoviae Radix (51), Astragali Radix and Atractylodis Macrocephalae Rhizoma (46), Atractylodis Macrocephalae Rhizoma and Saposhnikoviae Radix (43), Astragali Radix and Atractylodis Macrocephalae Rhizoma and Saposhnikoviae Radix (38), Forsythiae Fructus and Astragali Radix (37), and so on. In addition, 14 core combinations of medicines were obtained by complex system entropy cluster analysis, on this basis, six new prescriptions were screened out based on unsupervised entropy hierarchical clustering analysis. According to The Catalogue of Edible TraditionalChineseMedicinalMaterials, TraditionalChineseMedicinalMaterials for Health Food, and New Resources of Food published by National Health Commission of the People’s Republic of China, there are 35 species belonging to the group of edible traditionalChinesemedicinalmaterials, 20 species belonging to the group of new resources of food, 31 species belonging to the group of traditionalChinesemedicinalmaterials for health food, 19.11% of the preventive oral prescriptions for COVID-19 were composed of the medicines belonging to the above three groups. Besides, there are 11 toxic species, and 24.84% of the preventive oral prescriptions for COVID-19 contained toxic TCMs. ConclusionWe found that invigorating qi and resolving dampness were the main treatment used to prevent for COVID-19, combined with the methods for strengthening vital energy and eliminating pathogenic factors. Most of the preventive oral prescriptions for COVID-19 were treated in lung, spleen and stomach meridians. In the process of selecting prescriptions and using TCMs to prevent for COVID-19, the safety of preventive medicines was also emphasized. And the theory of “Preventive Treatment of Disease” was embodied in these preventive oral prescriptions for COVID-19. For the prescriptions containing toxic TCMs, specialattentionshould bepaidto their safety in clinical application.