董昌盛运用芳香类中药治疗肺结节规律
Regularity of Dong Changsheng's Application of Aromatic Traditional Chinese Medicine in the Treatment of Pulmonary Nodules
孙修桥 1伍睿昕 2楚晓 3符达 4马雨水 1张继亮 5韩睿钦 6董昌盛7
作者信息
- 1. 上海中医药大学附属龙华医院中医肿瘤研究所,上海 200032
- 2. 上海中医药大学附属上海市中医医院治未病科,上海 200071
- 3. 复旦大学附属上海市第五人民医院胸外科,上海 200240
- 4. 上海交通大学医学院附属瑞金医院胰腺中心,上海 200025
- 5. 北京同仁堂国药有限公司,香港 999077
- 6. 中国医学科学院基础医学科学研究所重大疾病共性机制研究全国重点实验室,北京 100005
- 7. 上海中医药大学附属龙华医院中医肿瘤研究所,上海 200032;上海中医药大学附属龙华医院肿瘤科,上海 200032
- 折叠
摘要
通过运用R语言分析了2017年1月1日至2023年11月30日于上海中医药大学附属龙华医院董昌盛专家门诊收集、筛选到的治疗肺结节的中药处方,得到了处方583首,其中使用芳香类中药92味,使用频次前3的芳香类中药为当归、川芎、川牛膝;关联规则分析得到以柴胡、人参、肉桂为核心的芳香药物组合;聚类分析得到以枳术汤和四物汤为主的核心处方;相关性分析得出大枣-干姜、连翘-神曲等关联性药对.结果表明芳香类中药在肺结节的治疗中应用广泛,体现了董昌盛医师调元解毒、芳香化湿的治疗原则,为芳香类中药的运用拓展提供借鉴和参考.
Abstract
Using R language to analyze the traditional Chinese medicine prescriptions for the treatment of pulmonary nodules collected and screened from January 1,2017 to November 30,2023 at Dong Changsheng Expert Clinic of Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine.583 prescriptions were obtained,using 92 aromatic traditional Chinese medicines.The top 3 aromatic traditional Chinese medicines with the highest frequency of use were Angelica sinensis,Ligusticum chanxiong Hort,and Cyathula officinalis kuan;The association rule analysis obtained a combination of aromatic drugs with Radix bupleuri,Panas sinserg,and Cinnamon cassia as the core;Cluster analysis revealed that the core prescriptions were mainly Zhizhu Tang and Siwu Tang;Correlation analysis showed that there were correlated drug pairs such as jujube dried ginger and Forsythia suspensa-Shenqu.The results indicate that aromatic traditional Chinese medicine is widely used in the treatment of pulmonary nodules,reflecting Dr.Dong Changsheng's treatment principles of regulating energy,detoxifying,and aromatizing dampness,providing reference and guidance for the expansion of the use of aromatic drugs.
关键词
董昌盛/芳香类中药/肺结节/用药规律/数据挖掘Key words
Dong Changsheng/aromatic traditional Chinese medicine/pulmonary nodule/medication pattern/data mining引用本文复制引用
基金项目
国家重点研发计划(2023YFC3503201)
国家自然科学基金(81403356)
上海市科委"科技创新行动计划"生物医药科技支撑专项(20S31904100)
上海市卫生健康委卫生行业临床研究专项(202040155)
上海中医药大学杏林青年学者培养计划(RC-2017-02-02)
出版年
2024
NETL
NSTL
维普
万方数据