| Objective:In this study,by collecting relevant medical records of Professor Wan Liling’s diagnosis and treatment of chronic cough,using the form of data mining,we explored the rules of medication for the treatment of chronic cough,in order to facilitate the learning and inheritance of her clinical experience and related academic ideas,and provide new guidance for further clinical practice.Method:Collect the standard chronic cough medical records diagnosed and treated by Professor Wan Liling from September 2018 to May 2020.After preprocessing the data,enter the medical records that meet the requirements into an Excel table and save them.After the entry is completed,a second inspection will be performed.Fixed an inspector to review the data and regularly check the accuracy of the data.After repeatedly confirming that the data is correct,count the patient’s gender and age,classification of drug efficacy,meridian of traditional Chinese medicine,drug frequency,etc.,and use SPSS modeler 18.0 for data association analysis,Cluster analysis,the statistical results obtained in the form of a chart are divided into columns and then discussed,and then their medication experience is summarized.Result:Included in 199 medical records,464 prescriptions,137 commonly used Chinese medicines and 39 high-frequency medicines were obtained.According to the general information statistics,the male to female ratio is close to 3:5,and the number of people aged 50-60 accounts for the largest proportion.The top ten in the frequency and percentage of drug efficacy are anti-cough and anti-asthmatic drugs,divergent wind-cold drugs,warming cold and phlegm drugs,invigorating qi drugs,qi promoting drugs,clearing heat and resolving phlegm drugs,dampness drugs,diverging wind-heat drugs,diuretic and swelling drugs,Heat-clearing and detoxifying drugs;the frequency of the four qi from high to low is warm,cold,calm,cool,and hot.Among them,the use frequency of warm medicine is nearly 60%;the frequency of five flavors of traditional Chinese medicine is pungent,bitter,and sweet from high to low.,Light,sour,astringent,salty;the top five Chinese medicines with the highest frequency of returning to menstruation are lung,stomach,liver,spleen,and heart;the top ten using Chinese medicines are bitter almond,platycodon,magnolia officinalis,licorice,Tangerine peel,ginger,inula,white front,aster,tuckahoe.Set a certain degree of support(20%)and confidence(80%)for high-frequency drugs using Apriori algorithm to analyze the association rules between drugs to obtain 597 pairs of drug combinations.Among them,the support of bitter almond and platycodon in the second-order association rule The highest,the confidence of bitter almond and Baiqian is the highest,the support of bitter almond,Magnolia officinalis and Platycodon grandiflorum in the third-order association rule is the highest,and the confidence of bitter almond,Magnolia officinalis and Baiqian is the highest;the core can be obtained after cluster analysis and statistics There are 13 groups of drug combinations,taking distance=23,39 high-frequency drugs can be grouped into 4categories,and 4 new prescriptions can be obtained.Conclusion:1.The drug combination and 4 prescriptions obtained through association rule analysis and cluster analysis have certain clinical use value.2.According to the analysis of data mining results,cold cough is the most common cause of chronic cough,and wind-cold is the main cause.In the treatment of Professor Wan Liling,the main method is “to warm the lungs and lower the qi to relieve cough”;“Xuan and drop are used together,the weight is lowered than the xuan”;“Replenishing and reducing the same tone,strengthening the defense first” is the main;3.Professor Wan Liling’s characteristic medicines for treating chronic cough include Bupleurum and Peucedanum,Inula and Loquat Leaf,Citrus aurantium and Citrus aurantium,Qingpi and Tangerine Peel;and it has a deeper effect on Magnolia officinalis and Houttuynia cordata. |
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