Exploring Chronic Atrophic Gastritis Based On The Dialectical Theory Of Syndrome Early Warning Factors Of Traditional Chinese Medicinee

Objective:Based on the method of TCM syndrome differentiation,to select the main risk factors of chronic atrophic gastritis from the basic information,living habits,medical history and clinical symptoms,and to select the early warning factors of CAG through logistic logistic regression analysis.Method:Outpatient or inpatient patients who underwent gastroscopy and pathological histological examination of gastric mucosa in the Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine(Acupuncture Hospital)from October 2021 to October 2022 were selected.Through structured questionnaire survey,we collected the clinical data of CAG patients,including basic information,living habits,medical history and clinical symptoms,integrated syndrome element integration and pathological typing,and the main risk factors for CAG were screened through univariate and multivariate logistic regression analysis.And determine the accuracy of dataset by ROC curve and ACC score.In the study,values less than 0.05 could be considered statistically significant.Result:A total of 199 patients were included in this study,including 71 patients with chronic atrophic gastritis and 128 patients with chronic non-atrophic gastritis.1.Basic information of patients in both groups Basic information,lifestyle habits and clinical symptoms were classified;and relevant types were classified.The gender,age,weight,lifestyle habits,clinical syndrome,sleep and stool were classified and recorded in the two groups.2.and univariate logistic regression analysis With CAG as the dependent variable and each factor as the independent variable,through univariate logistic regression analysis,pickled food,alcohol consumption,obesity,hyperlipidemia,vascular sclerosis,insomnia with polydreams,loose stool and Chinese medicine syndrome were selected as the main risk factors for CAG.3.Multivariate logistic regression analysis and validation With CAG as the dependent variable,The various factors were used as the independent variables,By multivariate logistic regression prediction model Y=(e(β1Xsymptom+∑β2Xanamnesis+∑β3Xthe nature of the disease+∑β4Xdrinking+∑β5Xpickled food+∑β6Xstool+∑β7Xsleep)/(1+e(β1Xsymptom+∑β2Xanamnesis+∑β3XThe nature of the disease+∑β4Xdrinking+∑β5Xpickled food+∑β6Xstool+∑β7Xsleep)),marled food,drinking alcohol,obesity,hyperlipidemia,vascular sclerosis,loose stool and TCM syndrome were selected as the seven main risk factors for CAG,in the present study,the calibration degree was evaluated by drawing the ROC diagram of the calibration curve,And,in the test data set,The test dataset accuracy was Acc=(TP+FN)/(TP+TN+FN+FP)≈94.8%,remeans that the multiple regression model has high accuracy,the selected risk factors are highly accurate for CAG onset,can be used as an early warning factor for CAG onset.Conclusion:1.Eating habits of pickled food,drinking alcohol,obesity,hyperlipidemia,vascular sclerosis,TCM syndrome differentiation of dampness and heat,and loose stool are the early warning factors about CAG.2.Univariate logistic regression analysis and multivariate logistic regression prediction model were used respectively.However,the selected risk factors have high accuracy for the onset of CAG,which can be used as the early warning factor of CAG onset to further guide early clinical screening,but it is recommended to further verify with large sample size.