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引用本文:周雨慧,李晓宁,张振强,芦锰.中成药治疗痴呆的成方规律分析[J].中国现代应用药学,2020,37(23):2883-2887.
ZHOU Yuhui,LI Xiaoning,ZHANG Zhenqiang,LU Meng.Analysis of the Prescription Law of Chinese Patent Medicine to Treat Dementia[J].Chin J Mod Appl Pharm(中国现代应用药学),2020,37(23):2883-2887.
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中成药治疗痴呆的成方规律分析
周雨慧1,2, 李晓宁2, 张振强1, 芦锰1,2
1.河南中医药大学, 郑州 450046;2.河北中医学院, 石家庄 050200
摘要:
目的 运用数据挖掘技术探究中成药治疗痴呆的用药规律,为指导临床用药及中成药的开发提供参考。方法 遴选并整理《国家中成药标准汇编》《中华人民共和国卫生部药品标准·中药成方制剂》《临床用药须知·中药成方制剂卷》2010年版和中国药典2015年版中收录的治疗痴呆的中成药,将符合纳入标准的药物录入Excel表数据库中,进行频数分析,并采用SPSS Statistics 23.0、SPSS Modeler 14.1统计软件对数据进行分析。结果 共纳入183个中成药,包含421味药物,出现频次较高的中药是熟地黄、当归、茯苓、枸杞子、人参,功效分类主要集中在补虚药,四气五味以甘、温为主,归经以五脏为主;关联规则分析中发现关联强度最高的药对组合7组,因子分析中共提取6个公因子,系统聚类分析中共得到4大类。结论 中成药治疗痴呆病症的用药规律呈现出补肾益精、活血化痰的共性。
关键词:  痴呆  中成药  用药规律  数据挖掘
DOI:10.13748/j.cnki.issn1007-7693.2020.23.012
分类号:R285.6
基金项目:河南省中医药科学研究专项重点课题(2018ZY1009);河南省高等学校重点科研项目计划(19A360021)
Analysis of the Prescription Law of Chinese Patent Medicine to Treat Dementia
ZHOU Yuhui1,2, LI Xiaoning2, ZHANG Zhenqiang1, LU Meng1,2
1.Henan University of Chinese Medicine, Zhengzhou 450046, China;2.Hebei College of Traditional Chinese Medicine, Shijiazhuang 050200, China
Abstract:
OBJECTIVE To explore the regularity of Chinese patent medicine to treat dementia by using data mining technology, and to provide reference for guiding the development of clinical medicine and Chinese patent medicine. METHODS Selected and sorted out the treatment of dementia included in the “National Standards of Traditional Chinese Medicines”, “Ministry of Health of the People's Republic of China Drug Standards·Traditional Chinese Medicine Preparations”, 2010 edition “Instructions for Clinical Use of Traditional Chinese Medicine Preparations”, 2015 edition “Chinese Pharmacopoeia”. For finished drugs, the drugs that meet the inclusion criteria were entered into an Excel spreadsheet database for frequency analysis, and the data were analyzed by SPSS Statistics 23.0 and SPSS Modeler 14.1 statistical software. RESULTS A total of 183 Chinese patent medicines were included, and the contained medicines had 421 flavors. The Chinese medicines with higher frequency were radix rehmanniae, angelica, poria, wolfberry, ginseng. Efficacy classification mainly focused on tonic drugs, four natures and five flavors were mainly sweet and warm, and the meridian mainly focused on the five internal organs. The association rule analysis revealed that there were 7 drug pair combinations with the highest association strength. Six common factors were extracted from the factor analysis. Four clusters were obtained from the systematic cluster analysis. CONCLUSION The regularity of Chinese patent medicines for the treatment of dementia shows the common features of nourishing the kidney and promoting essence, promoting blood circulation and removing phlegm.
Key words:  dementia  Chinese patent medicine  medication rules  data mining
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