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A Control Study Of Ancient Literature Data Of Low Back Pain And Modern Clinical Data Based On Big Data Analysis

Posted on:2019-10-02Degree:MasterType:Thesis
Country:ChinaCandidate:D FanFull Text:PDF
GTID:2394330566994907Subject:TCM History and Literature
Abstract/Summary:PDF Full Text Request
Objective: To study the distribution rule of syndrome drugs in lumbago and guide clinical prescription.Methods:(1)literature data study: through the Chinese medical code database to collect and collate 310 prescription data on the prescription of low back pain,and classify the syndrome type.IBM SPSS modeler 18 software was used to analyze the data,including frequency statistics,association analysis and cluster analysis.(2)real clinical data study: through the database of large data analysis system of Sichuan traditional Chinese medicine,7707 cases of low back pain records in the outpatient system from 2014 to 2017 were extracted.Through the same treatment method with the literature data,the pattern and drug rule of low back pain in real clinical data were summarized.(3)compare the statistical data between the literature data and the real clinical data.Results:(1)among the 510 literatures,the proportion of cold dampness syndrome and kidney yin deficiency syndrome was the largest.(2)among the 7707 real clinical data,the proportion of qi stagnation,blood stasis and kidney deficiency was the largest.(3)literature data on low back pain showed that most commonly used drugs were cinnamon,Achyranthes bidentata,Eucommia ulmoides,aconite root,angelica,Radix Angelicae Sinensis and Radix Glycyrrhizae.The most commonly used combinations were cinnamon and windbreak,Achyranthes bidentata and Dendrobium,cinnamon and Dendrobium,cinnamon and Rehmannia glutinosa,Eucommia ulmoides Oliver,Eucommia ulmoides and Dendrobium.(4)real clinical data showed that the most commonly used drugs were Achyranthes bidentata,Angelica sinensis,Eucommia ulmoides,Angelica pubescens,chuanxiong and licorice.The most commonly used combinations were angelica and safflower,angelica and Paeonia lactiflora,angelica and angelica,angelica and Gentiana,Gentiana macrophylla and safflower,Angelica pubescens and safflower.(5)The treatment of low back pain in ancient and modern times follows the theory of "Huangdi Neijing" with the theory of deficiency of liver and kidney,deficiency of Qi and blood,loss of nourishment of meridians and collaterals,and exogenous wind and cold and damp evil.Yin medicine.(6)the most commonly used drugs in each type and the most commonly used combination of the two groups of data on specific prescriptions were different.The distribution of various drugs in the treatment of low back pain was more uniform in the literature,and the real clinical data were biased according to the different types of drug use.Conclusion: the comparison of ancient literature data with real clinical clinical data shows that there is a common point in the thought of treatment,and there are differences in the main syndrome type,specific drug use and compatibility.Common ground: ancient and modern treatment of low back pain with warm tonifying liver and kidney,strong muscles and bones,and dispelling wind,cold and wet as the main train of thought.Differences:(1)the syndromes of low back pain in ancient literature are mainly cold dampness syndrome.(2)In ancient times,the drugs used to warm up the liver and kidney and the strong muscles and bones with the efficacy of dispelling wind and dampness were most common,and the distribution of the drugs was generally average in the distribution of warm yang,blood circulation,blood stasis,dispelling wind and relieving pain,invigorating Qi,invigorating the spleen,nourishing blood and nourishing Yin,and promoting qi and nourishing yin.Qi supplementing drugs and blood enriching drugs are the main drugs,while other drugs are relatively few.(3)In ancient prescriptions,the distribution of various types of drugs in the compatibility was more average,and the modern medicine was mostly to fill the liver and kidney and strong muscles and bones.
Keywords/Search Tags:low back pain, medication rules, big data analysis
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