Based On Data Mining To Explore The Experience Of Traditional Chinese Medicine Master Mei Guoqiang In Treating Renal Diseases

Objective: This study intends to conduct a preliminary retrospe ctive study of the clinical experience of the Chinese medicine master Mei Guoqiang in treating renal diseases through the meth od of data mining,excavate his clinical experience in treating renal diseases,and provide a certain reference for the clinic al treatment of renal diseases in Chinese medicine.Methods: This study was screened and sorted according to the established inclusion criteria and exclusion criteria.The subjects of the study were cases treated in the outpatient clinic of the Master of Traditional Chinese Medicine Studio of Hubei Provincial Hospital of Traditional Chinese Medicine from January2018 to December 2020.The Microsoft Excel software was used to analyze The data of the cases are entered one by one to form a database,and the terms in the medical records are standardized.IBM SPSS Statistics 21.0 is used to calculate the patient’s gender,age,symptoms,tongue,pulse,and frequency of traditional Chinese medicine used,the number of flavors and the frequency Perform frequency analysis on the nature and flavor of traditional Chinese medicines,etc.;according to the results of frequency analysis,set the frequency ≥ 75 times as high-frequency medicines,and use IBM SPSS Statistics 21.0 cluster analysis to classify the medicines after finishing the high-frequency Chinese medicines;Use IBM SPSS Modeler18.0 to perform multi-level correlation analysis on high-frequency Chinese medicine;explore the pairs of traditional Chinese medicine commonly used by Professor Mei,and draw a network diagram showing the correlation between high-frequency Chinese medicines,and explore the above-mentioned overall kidney disease On the basis of urinary tract infection with a large number of cases,further excavation is carried out,and finally the results obtained are analyzed and discussed.Results:(1)A total of 202 patients with renal diseases were enrolled in this study,including 108 males and 94 females.There are slightly more males than females.The ratio of male to female is about 1.13:1;the age distribution ranges from 5 to 83 years old.,The youngest is 5 years old and the oldest is 83 years old.The age distribution of patients is mainly 41-60 years old,with an average age of about 50.2 years old;the distribution of diseases is mostly urinary tract infection,gouty nephropathy,nephrotic syndrome,chronic glomerulonephritis,and sexual dysfunction.(2)In the collected cases,the common tongue quality is dark and red,and the common tongue coating is white and thick,the coating is slightly thicker,and the root in the coating is white and thick;the common pulse is slow pulse and slow pulse.,Pulse number,pulse number,etc.;the more common symptoms are frequent urination,poor sleep,narcosis,lower extremity edema,burning urination,urgency,palpitation,loose stools,increased nocturia,etc.;(3)This study involved a total of 425 prescriptions,using 222 traditional Chinese medicines such as Angelica,Chuanxiong,Pinellia,Citrus aurantium,Citrus aurantium,Coptis,Rhubarb,Fritillaria,Achyranthes bidentata,and the total frequency of medications reached 8071 times.Among them,there are a total of35 medicines with ≥75 times,and the total frequency is 5456 times,accounting for 67.6% of the total frequency of medication.According to the efficacy of traditional Chinese medicines,the 222 traditional Chinese medicines used can be divided into 18 categories.Heat-clearing medicines,tonic medicines,phlegm-relief and cough-relieving medicines,qi regulating medicines,diuresis and dampness medicines are mostly;the four qi of high-frequency medicines with a frequency of ≥75 times are mostly cold and warm;Mainly,the return meridian is mostly the liver meridian,spleen meridian,lung meridian,etc.;(4)Through cluster analysis,Chinese medicines with a higher frequency(frequency ≥75 times)can be divided into ten groups of medicines,namely the first group: Angelica and Chuanxiong;the second group: Pinellia ternata and Citrus aurantium;and the third group.Group: Smilax glabra,Rhubarb rhubarb,Fritillaria,Achyranthes bidentata;Group 4: Coptis,Evodia,Sea cuttlebone,Corydalis,Trichosanthes,Turmeric;Group 5: Euonymus,Turmeric,Hematoxylin,Acorus,Polygala,Pollen Typhae,Wulingzhi;Group 6:Black medicine,Fructus viciifolia,Phoenix-tail grass;Group 7:Jujube seed;Group 8: Scutellaria baicalensis,Poria cocos,Bupleurum,Tangerine peel;Group 9: Rhodiola,Astragalus;The tenth group: Cangzhu,Phellodendron amurense,Lysimachia,Haijinsha;(5)Through association analysis,it is concluded that Chuanxiong→ Angelica has the highest support in the second-order association rules,the rule association is 70.353%,and the confidence is 100%;the highest support in the third-order association rules is Citrus aurantium,French Pinellia→Coptis,the support degree is 52.0%,and the confidence degree is 80.995%;among the fourth-order association rules,the highest support degree is Pinellia ternata,Chuanxiong,Angelica→Fructus Aurantii,the support degree is50.824%,and the confidence degree is 80.556%.;(6)Results of data mining of urinary tract infection: Among patients with urinary tract infection,common symptoms include frequent urination,burning urination,poor sleep,shortness of breath,urgency,loose stools,fatigue,low back pain,incomplete urination,etc.;more frequent occurrences The tongue picture is white and thick,the texture is dark,the root is white,and the texture is red in the middle of the coating;more pulses appear as slow pulse;in the cases of urinary tract infection,a total of 93 prescriptions were collected,and the total frequency of drug use was 1804 times,of which the frequency of use was The higher drugs include Smilax glabra,Radix Aquilinum,Fritillaria vulgaris,Rhubarb,Achyranthes bidentata,Pinellia ternata,Fructus citrifolia,Ligusticum chuanxiong,Angelica sinensis,Citrus aurantium,Corydalis,Rhizoma Coptidis,Scutellaria baicalensis Georgi,Evodia,etc.;through cluster analysis and association analysis The commonly used drug combinations used by Professor Mei for the treatment of urinary tract infections are: Smilax glabra,Fritillaria,Achyranthes bidentata,Rhubarb,Radix Aquilinum,Citrus sinensis;Pinellia ternata,Citrus aurantium;Angelica,Ligusticum chuanxiong,Euphorbia chinensis;Atractylodes rhizome,Phellodendron amurense,Phoenix grass and so on.Conclusion: Professor Mei Guoqiang’s clinical experience in the treatment of renal diseases includes observing the pathogenesis and not restricting the syndromes;Tongyang is not warm;the combined use of traditional prescriptions is a new method;emphasis on phlegm and blood stasis;overall perpetual movement,emphasis on viscera relations.