| Objective:Section 1:To investigate the factors influencing the occurrence of single evidence elements in patients with T2DM and the specific effects of glucolipid metabolic indexes and thyroid function on the occurrence of their TCM evidence elements in patients with T2DM;Section 2:To investigate the correlation between thyroid function and glucose and lipid metabolic indices in patients with T2DM and the specific influence of each index;Section 3:To explore information on specific indicators of blood stasis evidence in T2DM and to try to explore its biological basis;Methods:1 Section 1:According to the standard of sodium excretion,the basic information and laboratory indexes of T2DM patients were collected,and the combination of single syndrome factors and syndrome factors were statistically analyzed.The method of binary Logistic regression analysis was used to take each single syndrome factor as dependent variable,and the basic condition,thyroid function and glucose and lipid metabolism index as independent variables for regression analysis.The stepwise regression method is used to screen the data to establish the model.2 Section 2:The basic information and laboratory indexes of the patients with T2DM were collected,and the basic conditions of the patients were statistically analyzed,and the pairwise correlation among the basic condition,thyroid function and glucose and lipid metabolism indexes of the patients with T2DM were analyzed.Then the indexes with significant correlation were analyzed by univariate or multiple regression analysis,and the stepwise regression method was used to screen the data to establish the model.And through the test method to verify the regression model.3 Section 3:According to the standard of nano-excretion,the basic information and laboratory indexes of T2DM patients were collected.According to whether they had blood stasis syndrome,they were divided into blood stasis syndrome group and non-blood stasis syndrome group.The indexes with significant correlation with T2DM blood stasis syndrome were selected from 44 laboratory indexes through correlation analysis.The neural network multilayer perceptron program was used to construct the prediction model of T2DM blood stasis syndrome,and the five-fold cross-validation method was used to verify the prediction model.Results:1 Section 1:The following results were found by statistical analysis of the TCM evidence elements and combinations of the elements in the 175 patients with T2DM:Yin deficiency was the most common evidence element in T2DM patients,and the combination of the five evidence elements was the most common,with deficiency-solid mixed evidence predominating.A dichotomous regression analysis of single evidence elements with underlying conditions and laboratory indicators revealed the following results.It was found that diastolic blood pressure was the main influencing factor for T2DM patients with yin deficiency;BMI was the main influencing factor for phlegm-dampness;age was the main influencing factor for blood stasis,junction-heat and water-dampness;TGAb was the main influencing factor for depression-heat and liver-yang;FT3 was the main influencing factor for qi deficiency;TRAb was the main influencing factor for phlegm-heat;TSH was the main influencing factor for yang deficiency;and gender was the main influencing factor for blood deficiency.The main influencing factor for the evidence of blood deficiency was gender,and the main influencing factor for the evidence of dampness was disease duration.2 Section 2:Through the statistical analysis of the general data of 175 patients with T2DM,the following results were found.The study found that 89 men and 86 women were included in the case,with the largest number of people aged between 50 and 59,and the largest number of people who were overweight.Eleven regression equations were obtained by univariate or multiple regression analysis of the correlation between basic condition and laboratory indexes in patients with T2DM:TT4=7.50918+0.13498 X HbAlc;FT3=4.07363+0.03575 X C-P0.01579 X age;FT4=0.81761+0.01570 X HbAlc;TSH=1.07612+0.12645×TG+0.24242×LDL;TC=3.78480+0.32175×TSH;TG=10-0.06616+0.04314×TSH+0.05526×C-P;HDL=1.55537-0.02371×C-P-0.01307×BMI;LDL=2.26751+0.17915 X TSH;HbAlc=100.76777+0.12889×FT4;C-P=-1.87744+0.15922 × TG+0.19312×BMI-0.00453× course of disease;INS=100.14207+0.03923×TG+0.03328×BMI。3 Section 3:Through the application of neural network multilayer perceptron program to build the prediction model of T2DM blood stasis syndrome,the following results are obtained.The accuracy of training and test samples in the model obtained by the study is 72%and 70.6%respectively.And in the prediction model of blood stasis syndrome of T2DM patients,the independent variables with more than 50%importance of standardization were Dmurd(100.0%),MPV(59.0%)and C-peptide(52.3%).Conclusions:1 Section 1:Increased diastolic blood pressure may increase the risk of Yin deficiency;increased BMI may increase the risk of phlegm-dampness;increased age may increase the risk of blood stasis,junctional heat and water-dampness;TGAb positive individuals may be more likely to suffer from depression-heat and liver-yang;increased FT3 within the normal range may decrease the risk of Qi deficiency;TRAb>0.3 within the normal range IU/mL may be more likely to suffer from phlegm-heat evidence;elevated TSH in the studied range may reduce the risk of Yang deficiency evidence;women may be more likely to suffer from blood deficiency evidence;prolonged disease duration may increase the risk of dampness and turbidity evidence.2 Section 2:Age,HbAlc,C-peptide,and TG levels of T2DM patients may affect their thyroid function;BMI,C-peptide,and TSH levels may affect their lipid metabolism;disease duration,BMI,FT4,and TG levels may affect their glucose metabolism.3 Section 3:D-D may be the discriminant index of blood stasis in T2DM,and D-D,MPV and C peptide may be the biological basis of blood stasis in T2DM. |
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