Results

Baseline Characteristics

A total of 540 patients were enrolled in the study (Table 1): 230 patients did not receive any hypoglycemic therapy, 100 patients received insulin therapy alone, 54 patients took glimepiride, 65 patients received metformin, and 91 patients received acarbose. There were 400 males (74.1%), 181 patients (33.5%) with AIS, and 359 patients (66.5%) with ACS.

Univariate linear regression analysis

First, univariate linear regression analysis was performed, and the following statistically significant candidate risk factors screened by p < 0.1 were included (as shown in Table 2): sex, age, body mass index (BMI), smoking, low-density lipoprotein (LDL), platelet count, CYP2C19*2, antiplatelet regimen and insulin.

Stratified regression analysis

Then, we adopted stratified regression to analyze the effects of hypoglycemic regimens on MAADP tested by TEG by adjusting for antiplatelet therapy regimens and demographic, genetic, biochemical, and lifestyle factors. By drawing a partial regression scatter plot and the scatter plot of the studentized residual and predicted values, a linear relationship between each risk factor and the square root of MAADP was determined.
Independent of each observation, values (Durbin-Watson test value is 1.928) were validated, and equal variance of data was confirmed by plotting the scatter plot between the studentized residual and the unnormalized predicted value.
The regression tolerance of all variables was greater than 0.1, and the variance inflation factors were less than 10; thus, there was no multicollinearity between variables. In the outlier test, there was no observed value where the studentized residual was greater than 3 times the standard deviations, data leverage values were less than 0.2, and there was no value where the Cook distance was greater than 1. The QQ diagram suggests that the research data satisfy the normal hypothesis.
After adjusting for candidate factors, we found that insulin therapy, antiplatelet therapy, sex, age, platelet count, and CYP2C19*2 were statistically significant. In the initial model, R2=0.016, F (4,534) = 2.181 (p = 0.070),only the hypoglycemic regimen (insulin therapy alone, sulfonylurea, metformin, acarbose) was included, and insulin alone was statistically significant (p = 0.009). After adjusting for antiplatelet therapy , in Model 2, R2 =0.028, F (5,534) = 3.042 (p = 0.010), insulin therapy (p =0.015) and antiplatelet therapy (p =0.012) were statistically significant. After Model 3 was corrected for demographic data and lifestyle-related factors (sex, age, BMI, smoking), R2 = 0.083, F (9, 530) = 5.325 (p < 0.001) insulin therapy (p =0.030) was still statistically significant; when we continued to compare physicochemical indexes (platelet count and LDL), insulin therapy (p =0.021) remained statistically significant, Model 4, R2 = 0.097, F (11,528) = 5.171 (p < 0.001). Finally, we corrected for the genetic factors (CYP2C19*2), and insulin therapy (p =0.036) remained statistically significant, Model 5, R2 =0.110, F (12, 527) = 5.432 (p < 0.001). In conclusion, after multiple factors were adjusted for, the effect of insulin therapy (p =0.036) on MAADP was always statistically significant. The specific results are shown in Table 3.