Medication Characteristics of Traditional Chinese Medicine in the Treatment of Patients with Community-Acquired Pneumonia Based on Data Mining
OBJECTIVE:To probe into the medication characteristics of traditional Chinese medicine in the treatment of community-acquired pneumonia.METHODS:According to the inclusion and exclusion criteria,the medical records of inpatients with community-acquired pneumonia from 2020 to 2023 were compiled and summarized,the frequency analysis,association rule analysis and complex network analysis on traditional Chinese medicines in the prescriptions were performed by data mining techniques.RESULTS:There were 71 prescriptions and 114 flavors of traditional Chinese medicine included in the study,with a total frequency of 902 times.Among the four Qi,coldness and flatness had the highest frequency,among the five flavors,bitterness,sweetness and pungency had the highest frequency,among the channel tropism,lung,stomach and spleen channels had the highest frequency.Among the drug categories,the phlegm-reducing,cough-relieving and asthma-relieving drugs,heat-clearing drugs,deficiency tonic drugs and antidepressant drugs took the lead.The drug combination association rules showed that Asteris radix et rhizoma-Cynanchistauntonii rhizoma et radix,Phragmitis rhizoma-Persicae semen,Asteris radix et rhizoma-Farfarae flos,Forsythiae fructus-Lonicerae japonicae flos,Phragmitis rhizoma-Figwort root,Phragmitis rhizoma-lophatherum gracile were the commonly used traditional Chinese medocone.One core prescription extracted was Amygdalus communis vas,Fritillariae Thunbrgii Bulbus,Platycodon Grandiforus,Eriobotryae Folium,Phragmitis rhizoma,Asteris radix et rhizoma,Scutellariae Radix and licorice.CONCLUSIONS:Preliminary understanding for medication characteristics of traditional Chinese medicine in the treatment of community-acquired pneumonia provides a certain reference basis for clinical identification and treatment of community-acquired pneumonia.
Data miningCommunity acquired pneumoniaTraditional Chinese medicineMedication characteristics
万方数据
维普
