摘要
目的研究新安医家程有功《冯塘医案》辨治肺系疾病的相关理论思想,以期揭示其用药规律。方法结合《内经》、《景岳全书》等相关论述论著,运用SPSS 17.0对用药情况进行相关数据挖掘分析,阐述程氏辨治肺系疾病经验,综合分析其辨治方药规律特色。结果由频数分析发现,在治疗虚损药物中,川贝、茯苓、麦冬用量较多;在药性方面,主要集中于平、温、寒三类;在药味方面,以甘、苦、辛为主;在归经方面,主要归于肺、肾、肝经。对前22味核心药物进行系统聚类分析,分析共得出药对组合7组,3味药组合4组,4味药组合3组。结论程氏擅治杂病和虚损,对于养阴益气法治疗肺系疾病,考镜源流,综各家之长,语言不虚不燥,论述有理有据,辨治特色鲜明,治法方药特色突出,对于临床指导和后世学习有很大意义。
Objective To study the theory of Feng Tong Medical Case in the treatment of pulmonary disease by Xinan doctor Cheng Yougong,so as to reveal the law of medicine. Methods Based on Neijing,Jingyue Encyclopedia and other related works,SPSS 17. 0 was used to analyze related data,elaborate Cheng Shi experience in treating pulmonary disease and analyze comprehensively the characteristics of syndrome differentiation formulas. Results Frequency analysis showed that in the treatment of the deficiency drugs,more sichuan bay,tuber,and wheat were used. In terms of medicinal properties,they mainly focused on the three categories: moderate,warm and cold. In terms of medicine flavor,they mainly focused on sweetness,bitterness and piquancy. In terms of the meridian,they mainly focused on lung,kidney and liver. Based on the system cluster analysis of the former 22 core drugs,7 groups of pair combinations,4 groups of three-flavor combinations and 3 groups of four-flavor combinations were obtained. Conclusion Cheng Shi treatment is good at miscellaneous diseases and deficiency. The method of nourishing Yin and supplementing Qi is used in the treatment of lung disease,which examines the mirror source and course,combines the advantages of various theories. The language is neither empty nor dry; the argument is reasonable and justified; the treatment is distinctive; the prescription is outstanding,which is of great significance for clinical guidance and the later study.
出处
《锦州医科大学学报》
CAS
2017年第6期90-93,共4页
Journal of Jinzhou Medical University
基金
安徽中医药大学2016年大学生创新创业项目
编号:2016077
关键词
冯塘医案
程有功
养阴益气法
肺系疾病
文献研究
新安医学
聚类分析
feng tong medical case
Cheng Yougong
the method of nourishing Yin and supplementing Qi
lung disease
literature research
Xinan medicine
clustering analysis