摘要
目的:基于《伤寒杂病论》探讨葛根的应用规律,为临床应用提供借鉴。方法:系统梳理《伤寒杂病论》中含有葛根的方剂,采用SPSS 20.0统计软件单因素逻辑回归分析及二元相关性分析葛根剂量与相关因素之间关系。结果:《伤寒杂病论》中含有葛根的方剂共6首。二元相关性分析显示,葛根单次用量与葛根的药味数、服用次数有关,有统计学意义(P=0.007,P=0.032)。单因素逻辑回归分析显示,葛根是否为主药与葛根单次用量、葛根的剂量、药味数量、用水量、剩余水量、每次服用水量和服用次数无相关性(P>0.05)。6首含有葛根的方剂中,葛根单次用量平均为6.28 g,即葛根的实际服用剂量为3.31~14.35 g(相当于3~14 g)。结论:从量效关系可以发现葛根的使用不存在显著的量效关系,其用量和功效较为稳定,为临床应用提供了坚实的依据。
Objective:To explore the dose-effect relationship and medication rule of Gegen(葛根)(Radix Puerariae)based on Treatise on Typhoid and Miscellaneous Diseases.Methods:The prescriptions containing Gegen(Radix Puerariae)in Treatise on Typhoid and Miscellaneous Diseases were systemically combed.The single factor Logistic regression analysis and binary correlation analysis were used to analyze the relationship between the dose of Gegen(Radix Puerariae)and related factors.Results:There were 6 prescriptions of Pueraria in in Treatise on Typhoid and Miscellaneous Diseases.Binary correlation analysis showed that the single dose of Gegen(Radix Puerariae)was related to the number of taste and times of taking Pueraria,which was statistically significant(P=0.007,P=0.032).Single factor Logistic regression analysis showed that whether Pueraria was the main drug or not had no correlation with single dosage,dosage,taste quantity,water consumption,residual water,water consumption per time and times of taking Pueraria(P>0.05).Among the six prescriptions containing Gegen(Radix Puerariae),the average single dose of Gegen(Radix Puerariae)was 6.28g,the actual dose of Gegen(Radix Puerariae)was 3.31-14.35 g(equal to 3-14 g).Conclusion:It can be found that there is no significant dose effect relationship in the use of Pueraria,and its dosage and efficacy are relatively stable,which provides a solid basis for clinical application.
作者
樊俐慧
张伟
王志刚
杨霞
Fan Lihui;Zhang Wei;Wang Zhigang;Yang Xia
出处
《中医临床研究》
2021年第21期28-30,共3页
Clinical Journal Of Chinese Medicine
基金
国家自然科学基金资助项目(8167150826)
甘肃省中医药管理局中医药防治重大疾病科研课题(2018ZD04)。
关键词
葛根
伤寒杂病论
量效关系
二元相关性分析
单因素逻辑回归分析
Gegen(Radix Puerariae)
Treatise on Typhoid and Miscellaneous Diseases
Dose-effect relationship
Binary correlation analysis
Single factor logistic regression analysis
