| 引用本文: | 陈亚楠,朱星昊,苗明三,孙旭,刘怀民.中医药防治新型冠状病毒肺炎的用药规律分析[J].中国现代应用药学,2020,37(5):542-548. |
| CHEN Yanan,ZHU Xinghao,MIAO Mingsan,SUN Xu,LIU Huaimin.Analysis of Chinese Medicine Regularity for Preventing and Treating COVID-19[J].Chin J Mod Appl Pharm(中国现代应用药学),2020,37(5):542-548. |
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| 摘要: |
| 目的 基于关联规则、因子分析和聚类分析探讨中医药防治新型冠状病毒肺炎（COVID-19）的用药规律，为COVID-19的中医药临床预防、治疗提供用药参考。方法 搜集2020年1月中医药介入COVID-19治疗起全国各地区、各名家所提供的中医药治疗方案，排除食疗方、香囊方，仅收集预防方和治疗方，建立数据库进行统计分析，并依据中国药典2015年版对所纳中药进行药性、药味及归经分类。使用Excel 2016、Clementine 12.0、SPSS Statistics 21.0统计软件对纳入的中药进行关联规则分析、因子分析和聚类分析。结果 共纳入101份方剂，共计中药163味，出现频数974次。在纳入数据库的101份方剂中，出现频次≥10的中药有28种、频次≥15的中药有14种，频次最高的前3味药为甘草、金银花和连翘；总体来看，药物功效及分类以清热药、补虚药和解表药最为常见；性味及归经中，药性占寒性、温性和平性3种；药味以苦味、甘味及辛味最多，占总药味的96.91%；归经以归肺经、胃经和脾经为主。通过关联规则分析得到9种关联强度最高的药对组合，通过因子分析得出5个因子，聚类分析则提取出3个聚类。结论 COVID-19中医药防治常用的中药以清热药为主，且与补虚及解表药合用可起到很好的防病治病效果。 |
| 关键词: 新型冠状病毒肺炎 中医药 性味归经 药对 配伍 关联规则 因子分析 聚类分析 |
| DOI：10.13748/j.cnki.issn1007-7693.2020.05.005 |
| 分类号:R978.7 |
| 基金项目:国家中医药管理局第四批全国中医优秀人才研修项目（国中医药人教发[2017]24号） |
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| Analysis of Chinese Medicine Regularity for Preventing and Treating COVID-19 |
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CHEN Yanan1, ZHU Xinghao1, MIAO Mingsan1, SUN Xu2, LIU Huaimin2
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1.Henan University of Chinese Medicine, Zhengzhou 450046, China;2.Affiliated Tumor Hospital of Zhengzhou University, Henan Provincial Cancer Hospital, Zhengzhou 450008, China
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| Abstract: |
| OBJECTIVE To explore the rules of traditional Chinese medicine for prevention and treatment of COVID-19 based on association rules, factor analysis and cluster analysis, in order to provide reference for COVID-19 clinical prevention and treatment of traditional Chinese medicine. METHODS From late January 2020, when TCM interventional COVID-19 treatment was started, the Chinese medicine treatment plans given by various regions and famous doctors in the country were collected. The dietary and sachet prescriptions were excluded, only the preventive and therapeutic prescriptions were collected, and established a database for statistical analysis. Used the 2015 edition of the Chinese Pharmacopoeia to classify the medicinal properties of traditional Chinese medicines. Used Excel 2016, Clementine 12.0, SPSS Statistics 21.0 statistical software to analyze association rules, factor analysis and cluster analysis of the included Chinese medicines. RESULTS A total of 101 prescriptions, 163 flavors of traditional Chinese medicine, and a frequency of 974 occurrences were included in this statistic. Among the 101 prescriptions included in the database: 28 kinds of Chinese medicines with a frequency of ≥10 and 14 kinds of Chinese medicines with a frequency of ≥15. The top three drugs with the highest frequency were licorice, honeysuckle and forsythia. Over all, the efficacy and classification of antipyretics, tonics and antihypertensive drugs were the most common. Among nature and flavor, and channel tropism, there were cold in nature, warm in nature, and neutral in nature. The bitter, sweet and astringent flavors account for 96.91% of the total medicinal flavors, and the meridians were attributed to the lung, stomach and spleen mainly. Nine couplet medicines combinations with the highest correlation strength were obtained through the association rule analysis. Five factors were obtained through factor analysis. And three clusters were extracted through cluster analysis. CONCLUSION The traditional Chinese medicine for the prevention and treatment of COVID-19 is mainly heat-clearing medicine, and combined with tonic and antipyretic drugs can have a good effect in preventing and treating diseases. |
| Key words: COVID-19 traditional Chinese medicine sexual flavor meridian couplet medicines concerted application association rules factor analysis cluster analysis |
