文献类型：期刊文献

中文题名：《四部医典》痰诊法定量化研究

英文题名：Quantitative study on sputum diagnosis method in Four Medical Canons

作者：公保甲[1,2];英木草[3];羊措吉[2];贡保东知[2];尼玛次仁[1];米玛旺堆[4]

第一作者：公保甲

机构：[1]西藏藏医药大学,拉萨850000;[2]甘肃中医药大学藏医学院,甘肃合作747000;[3]碌曲县玛艾镇社区卫生服务中心,甘肃碌曲747200;[4]西藏大学生态环境学院,拉萨850000

第一机构：西藏藏医药大学,拉萨850000

年份：2024

卷号：39

期号：10

起止页码：5432

中文期刊名：中华中医药杂志

外文期刊名：China Journal of Traditional Chinese Medicine and Pharmacy

收录：CSTPCD;;北大核心:【北大核心2023】；CSCD:【CSCD2023_2024】；

基金：西藏藏医药大学2023年度博士研究生科研创新能力提高项目(No.BSDJS-BS-2023006);甘肃中医药大学2024年甘肃(甘南)藏医药“医-药-护”研究与转化协同创新中心科研项目。

语种：中文

中文关键词：《四部医典》;藏医;痰诊法;冗余分析法

外文关键词：Four Medical Canons;Tibetan medicine;Phlegm diagnosis method;Redundancy analysis method

摘要：目的:对《四部医典》中痰诊法进行定量化研究。方法:以“痰(■)”和“咳(■)”为关键词搜集痰诊法相关内容,采用Excel整理数据、R统计软件中借助vegan包进行冗余分析法。对《四部医典》中有关痰诊法的内容进行研究分析。结果:痰诊对象按疾病性质以赤巴病和恶血病为主;按疾病部位以肺部及全身性为主,通过咳嗽时间点与泡沫可以确定隆病;痰色与混合物可鉴别赤巴病;痰量与稀稠可鉴别培根病。结论:藏医痰诊法对疾病的诊断与鉴别具有重要意义,但尚未形成系统化,具有很大的研究空间。
Objective:To quantitatively study the phlegm diagnosis method in Four Medical Canons.Methods:The relevant contents of phlegm diagnosis method was collected by the keywords‘phlegm(■)’and‘cough(■)’,and the redundancy analysis method was conducted by Excel data collation and R statistical software with vegan package(RDA:redundancy analysis).To explore the contents of the phlegm diagnosis method in Four Medical Canons,and to provide a scientific basis for Tibetan medicine for the diagnosis and differentiation of diseases in the future.Results:The object of phlegm diagnosis method is mainly chibiasis and cachemia according to the nature of the disease;the disease site is mainly lung and systemic according to the location of the disease;and the Long disease can be determined by cough time point and foam;Chibiasis could be determined by sputum color and mixture;Bacon disease could be determined by sputum volume and consistency.Conclusion:The method of Tibetan phlegm diagnosis is of great significance for the diagnosis and differentiation of diseases,but the systematic phlegm diagnosis method of Tibetan medicine has great research space.