Baseline and biochemical properties
Based on Additional file 1, in Table S1, baseline characteristics were compared in the control and patient groups. Systolic blood pressure, and diastolic blood pressure and lipid profiles were significantly higher in the diabetic atherosclerosis patients (DAP) group than in the diabetic patients (DP) group. Also, the frequency of smoking, hypertension, hyperlipidemia, coronary artery disease, and chronic renal failure was significantly higher in the DAP group.
sd-LDL, MDA, TCA , AOPP and atherogenic indices in patient and control groups
The sd-LDL, MDA, TCA, and AOPP variables and the atherogenic indices were compared in both groups (Additional file 1, Table S2). The sd-LDL concentration in DAP group was significantly higher than DP group (31.47 ± 11.71 vs. 13.51 ± 5.58, P <0.001). The MDA level in DAP group was significantly higher than DP group (41.79 ± 24.75 vs. 28.62 ± 14.68, P <0.001). The TCA level in DAP group was significantly lower than DP group (606.77 ± 238.20 vs. 831.56 ± 331.14, P <0.001). Also, the AOPP amount in DAP group was significantly higher than DP group (56.94 ± 27.37 vs. 45.47 ± 17.75, P <0.001). In addition, AIP, CRI-I, CRI-II, AC, NHC, and TYG levels were significantly higher in DAP group (P <0.001, Table S2).
Sd-LDL, MDA, TCA , AOPP and atherogenic indices in patient with CAD, with CRF and with HTN
As figure 1, patients with chronic renal failure (CRF) had higher FBS, MDA and AOPPs levels compared than patients without CRF. Also, FBS, MDA and sd-LDL levels were higher in patients with hypertension (HTN). In addition, patients with coronary artery disease (CAD) had FBS and sd-LDL levels more than patients without CAD.
Simultaneous effects of age, medical history, atherogenic indices on atherosclerosis
As shown in Table 1, the incidence of atherosclerosis was assessed using logistic regression. With each unit increase in TYG and AIP, the chance of developing atherosclerosis significantly increases 19.9 and 12.05 times, respectively (P <0.05). And, with each unit enhancement in AC, CRI-I, sd-LDL, MDA, AOPPs, and NHC, the chance of developing atherosclerosis increases 1.77, 1.60, 1.27, 1.038, 1.022, and 1.013 times, respectively (P <0.05). These rates were statistically significant. With each unit increase in TCA, the chance of developing atherosclerosis significantly decreases 0.995 times.
With each passing year, the chances of developing atherosclerosis significantly enhance 1.08 times. Having a history of high blood pressure and dyslipidemia significantly increases the chance of developing atherosclerosis by 13.22 and 4.77 times, respectively (P<0.05). Smoking increases the chances of developing atherosclerosis by 3.54 times. This amount was significant.
Relationship between sd-LDL, MDA, AOPPs, TCA FBS, atherogenic indices in diabetic atherosclerosis patients
The prediction interaction model was calculated by receiver operating characteristics (ROC) analysis and area under the curve (AUC). The AUC determined from the ROC curve of a model comprising atherosclerosis markers as predictor variables exhibited higher values (AUC: sd-LDL =0.924), (AUC: TYG= 0.866), (AUC: CRI-I= 0.772), (AUC: AC= 0.770), (AUC: AIP= 0.769), (AUC: NHC= 0.709), (AUC: TCA= 0.708), (AUC: MDA: 0.654), and (AUC: AOPP= 0.610). The sensitivity and specificity of these biomarkers were determined (Figure 2 and Additional file 1 in Table S3). The best predictors were sd-LDL with sensitivity (64.41±33.87) and specificity (73.84±32.62) and TYG with sensitivity (63.75±30.32) and specificity (72.10±31.23).
As Additional file 1, Figure S1 shows the correlation between factors. sd-LDL was significantly correlated with AIP (r= 0.28, P= 0.002), with CRI-I (r= 0.28, P= 0.002), with NHC (r= 0.20, P=0.02), with AC (r= 0.26, P=0.005), with TYG (r= 0.42, P<0.0001), and with TCA (r= 0.29, P= 0.001). The MDA has a positive and significant relationship with NHC (r: 0.23, P= 0.01) and AC (r: 0.21, P= 0.02). In addition, the relationship between TCA with AOPP (r: -0.21 P= 0.02) was significantly negative.