The background characteristics of the subjects are shown in Table 1. We compared the AAC score and the AAC length between groups with and those without a history of CAD, CI, or PAD. Representative images of the AAC scores and AAC lengths are shown in Fig. 1 (see details in Research design and methods). The AAC scores and the AAC lengths in the group with CAD and the group with CI were significantly higher than those in the corresponding groups without these diseases (Fig. 2). The AAC score and the AAC length in the group with PAD were higher than those in the group without PAD, but the difference in AAC length did not reach statistical significance (Fig. 2). We evaluated whether the AAC score and the AAC length were independently associated with CAD, CI, and PAD using multiple regression linear analyses after adjustments for known arteriosclerotic risk factors (age, duration of diabetes, BMI, SBP, DBP, alcohol intake, smoking, HbA1c, 2-hour postprandial plasma glucose, eGFR, LDL-C, HDL-C, TG, hsCRP) (Table 2). Both the AAC score and the AAC length showed independent associations with both the CAD history and the CI history, while only the AAC length was independently associated with PAD.
Next, we investigated the association of AAC levels with various parameters (Table 3). The AAC score and the AAC length were positively correlated with age, duration of diabetes, Fib4-index, sCr, HDL-C, corrected Ca, baPWV, and peripheral neuropathy and were inversely correlated with BMI, DBP, HbA1c, 2-hour postprandial CPR, ALT, eGFR, LDL-C, and hsCRP. Negative correlations with fasting CPR, γ-GTP, and triglyceride were significant for the AAC score, while the trends did not reach significance for AAC length. Age, duration of diabetes, BMI, Fib4-index and baPWV showed relatively strong associations with the AAC score and the AAC length. Of note, known cardiovascular risk factors including BMI, DBP, LDL-C, HDL-C, and hsCRP were inversely correlated with AAC.
Next, we further analyzed the correlation between BMI and the AAC score or AAC length using a multiple linear regression analysis after adjustments for potential arteriosclerosis risk factors (age, duration of diabetes, BMI, SBP, DBP, alcohol intake, smoking, HbA1c, 2-hour postprandial plasma glucose, eGFR, LDL-C, HDL-C, TG and hsCRP). In the final model, postprandial CPR, corrected Ca, peripheral neuropathy, and the Fib4-index were entered as independent variables (Table 4). The significance of an association between a lower BMI and an increased AAC score was maintained, although that with the AAC length disappeared after adjustments for gender and age.
The Fib4-index was another notable factor associated with AAC levels, as shown in Table 3. We next investigated the further associations of the Fib4-index with the AAC score and the AAC length using multiple linear regression analyses after adjustments for age, duration of diabetes, BMI, SBP, DBP, alcohol intake, history of smoking, HbA1c, 2-hour postprandial plasma glucose, eGFR, LDL-C, HDL-C, TG, hsCRP, postprandial CPR, corrected Ca, and peripheral neuropathy (Table 5). The Fib4-index remained positively associated with both the AAC score and the AAC length in a significant manner. Type 2 diabetes patients frequently have non-alcoholic fatty liver disease (NAFLD), which includes non-progressive non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH) with progressive inflammation and liver fibrosis. The Fib-4 index is a scoring system used to predict liver fibrosis in patients with NAFLD. We next extracted patients who had undergone an abdominal ultrasonography examination within 6 months before and after hospitalization and assessed the relationship between fatty liver and the AAC score and AAC length. The AAC score and the AAC length were not significantly different between patients with and those without fatty liver (Fig. 3A). An analysis of the AAC score and the AAC length for each Fib-4 index level (<1.3 predicts no fibrosis, >2.67 predicts fibrosis) in the group with and the group without fatty liver showed a more evident trend toward an increasing AAC score and AAC length in patients with a high Fib-4 index in the group without fatty liver (Fig. 3B). Similar trends were observed in an analysis using the Forns index, which is another liver fibrosis scoring system (Fig. 3C). A multiple regression analysis after adjustment for the presence or absence of fatty liver showed that the correlation of the Fib-4 index with the AAC score and the AAC length was independent of the presence of fatty liver (β=0.280, p=0.027, N=65).
Multiple linear regression analyses demonstrated that the correlations of HDL-C and hsCRP were diminished after adjustment for age and that the correlations of DBP, LDL-C, corrected Ca, and peripheral neuropathy were diminished after adjustments for age, gender, and duration of diabetes. The correlation of postprandial CPR remained significant after adjustments for these three variables and was diminished after additional adjustments for BMI (data not shown).