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.