摘要
目的运用数据挖掘与文献可视化分析探讨中医药治疗矮小症的用药规律和文献研究现状、热点及发展趋势,为拓宽矮小症中医辨证论治思路提供参考。方法收集中国知网、万方数据库、维普中文科技期刊数据库建库至2023年4月收录的中医治疗矮小症医案,对信息进行规范化处理后使用Excel 2016建立数据库。利用古今医案云平台(V2.2.3)统计矮小症患者舌苔、脉象、疾病证型与证素及治疗所用中药的频次、功效、气味归经,并对核心中药进行聚类和复杂网络分析。此外,以矮小症为关键词检索1993-2023年发表在上述数据库的文献,运用CiteSpace对发文量与关键词进行可视化分析。结果对58篇文献中58位矮小症患者的58则医案进行数据挖掘。患者多见舌淡苔薄白,脉细。矮小症证型以脾肾气虚证为主,病位在肾、脾、肝,病性多虚。共纳入58个方剂158味中药,累积用药频次831次,使用频率前5的核心中药为茯苓、山药、陈皮、太子参、熟地黄,共奏生津益肺、补益肝肾、理气健脾之效,药性多平温,味甘苦,归经脾、肾、肺经。K-Means聚类算法将30味高频中药聚为7类。复杂网络分析显示核心治疗组方为茯苓-山药-陈皮-太子参。此外,共检索到矮小症文献1239篇,最终纳入1211篇进行文献可视化分析。矮小症文献年发文量逐年呈上升趋势。关键词共现和聚类分析显示矮小症、生长激素和儿童是主要关键词,骨代谢、生长发育和骨密度是研究热点。结论脾肾气虚证是矮小症的主要证型,临床常用茯苓、山药、陈皮、太子参等配伍治疗。2016年至今,矮小症的研究增长迅速,聚焦于儿童生长激素与骨代谢。
Objective To explore the medication rules and literature research status,hotspots and development trend of traditional Chinese medicine treatment(TCM)of short stature by using data mining and literature visualization analysis,and to provide a reference for broadening the ideas of TCM diagnosis and treatment.Methods Medical cases of TCM for short stature included in China National Knowledge Infrastructure,Wanfang Database and Chongqing VIP Information Company Limited until April 2023 were collected,and a database was established with using Excel 2016 after normalising the information.The ancient and modern medical records cloud platform(V2.2.3)was used to count the tongue coating and pulse condition of the patients,syndrome type and elements of disease,and the frequency,efficacy,odor and meridian tropism of Chinese medicine,which was used in treating patients with short stature,and the core Chinese medicine was clustered and analyzed by complex networks.In addition,the literature published in the above databases from 1993-2023 was searched with using short stature as a keyword,and CiteSpace was used to visualise and analyse the number of publications and keywords.Results Data mining was performed on 58 medical cases of 58 patients with short stature from 58 literature.The patients were mostly seen to have a common tongue,thin white fur and fine pulse.Diseases were predominantly spleen-kidney qi deficiency syndrome,with disease sites in the kidney,spleen and liver,and the nature of the disease was mostly deficient.A total of 158 Chinese herbal medicines were included in 58 formulas,with a cumulative medication frequency of 831 times.The core Chinese medicines with the top 5 frequency of use,Fuling,Shanyao,Chenpi,Taizishen and Shudi-Huang,had the effects of engendering fluid and benefiting the lungs,nourishing the liver and kidneys,and regulating the qi and strengthening the spleen,with mostly flat and warming medicinal properties and a sweet and bitter flavour,and belonged to the spleen,kidney,lung meridians.The 30 high-frequency Chinese herbal medicines were clustered into 7 classes by the K-Means clustering algorithm.Complex network analysis showed that the core therapeutic grouping was Fuling-Shanyao-Chenpi-Taizishen.Additionally,a total of 1,239 literature articles on short stature were retrieved,and 1211 articles were finally included for literature visualisation analysis.The annual number of publications on short stature showed an increasing trend.Keyword co-occurrence and cluster analysis showed that short stature,growth hormone and children were the main keywords,and bone metabolism,growth and development and bone density were the research hotspots.Conclusion Spleen and kidney qi deficiency syndrome is the main syndrome type of dwarfism,which is commonly treated with a combination of Poria cocos,yam,tangerine peeland Radix Pseudostellariae in clinical practice.Since 2016,research on dwarfism has grown rapidly,focusing on growth hormone and bone metabolism in children.
作者
黄栎颖
王诗琪
潘赐明
戴凯
吕卓
陈文慧
HUANG Liying;WANG Shiqi;PAN Ciming;DAI Kai;LV Zhuo;CHEN Wenhui(Yunnan University of Traditional Chinese Medicine School of Basic Medicine,Kunming 650500,China;Anhui Agricultural University,Hefei 230036,China;Department of Pediatrics,Zhenxiong County Traditional Chinese Medicine Hospital,Zhaotong Yunnan 657200,China)
出处
《新疆医科大学学报》
CAS
2023年第11期1519-1525,共7页
Journal of Xinjiang Medical University
基金
国家自然科学基金项目(82160898)。
关键词
矮小症
数据挖掘
用药规律
可视化分析
short stature
data mining
medication rules
visualization analysis
