Best multiple logistic regression model for predicting silent myocardial ischemia.

<p>Best multiple logistic regression model for predicting silent myocardial ischemia.</p

Unadjusted odds ratio for the presence of SMI (univariate analysis).

<p>Unadjusted odds ratio for the presence of SMI (univariate analysis).</p

ROC curves to detect Silent Myocardial Ischemia (SMI).

<p>The area under the curve (AUC) of the three risk scores tended to underestimate SMI risk when compared with our proposed model. <b>1A)</b> Comparison with the Framingham Risk Score [0.833 (95% CI: 0.692–0.974) vs. 0.688 (95% CI: 0.545–0.830, p = 0.122)]. <b>1B)</b> Comparison with the UKPDS Risk Score [0.833 (95% CI: 0.692–0.974) vs. 0.559 (95% CI: 0.424–0.693), p = 0.001]. <b>1C)</b> Comparison with the EDC Risk Score [0.833 (95% CI: 0.692–0.974) vs. 0.558 (95% CI: 0.352–0.763), p = 0.027].</p

Clinical and metabolic characteristics of patients with type 1 diabetes.

<p>Clinical and metabolic characteristics of patients with type 1 diabetes.</p

Clinical characteristics of study population.

<p>Data are given as percentages, mean (SD) or median (interquartile range). CHD: Coronary heart disease. T2DM: type 2 diabetes. T1DM: type 1 diabetes. BMI: body mass index. WHR: waist-to-hip ratio. eGFR: estimation of glomerular filtration rate. ACR: Urinary albumin to creatinine ratio. PTH: parathyroid hormone. 25(OH)D: 25-hydroxy-vitamin D. FGF-23: Fibroblast growth factor 23. hsCRP: high-sensitivity C-reactive protein. IL-6: interleukin 6. sTNFαR1: soluble fraction of tumor necrosis factor α receptor 1. sTNFαR2: soluble fraction of tumor necrosis factor α receptor 2. ICAM-1: soluble intercellular adhesion molecule-1. VCAM-1: soluble vascular cell adhesion molecule-1. aPWV: aortic pulse wave velocity.</p><p>Clinical characteristics of study population.</p

Association of FGF-23 with aPWV in the patients with T1DM.

<p>Model 1 adjusted for age, sex, eGFR, current smoking (No/Yes), arterial hypertension (No/Yes), dyslipidaemia (No/Yes), BMI and FGF-23. Model 2 adjusted for covariates in model 1 and variables reflecting mineral metabolism (calcium, phosphate, PTH and 25(OH)D). Model 3 adjusted for covariates in model 2 and duration of diabetes (years) and the presence of microvascular complications (diabetic retinopathy, nephropathy and peripheral polyneuropathy) and low-grade inflammation general score and endothelial dysfunction score. 25(OH)D were additionally adjusted for seasonality.</p><p>Association of FGF-23 with aPWV in the patients with T1DM.</p

Association of FGF-23 with aPWV in the control group.

<p>Model 1 adjusted for age, sex (male/female), eGFR, current smoking (No/Yes), arterial hypertension (No/Yes), dyslipidaemia (No/Yes), BMI and FGF-23. Model 2 adjusted for covariates in model 1 and reflecting mineral metabolism (calcium, phosphate, PTH and 25(OH)D). Model 3 adjusted for covariates in model 2 and low-grade inflammation general score and ED score. 25(OH)D were additionally adjusted for seasonality.</p><p>Association of FGF-23 with aPWV in the control group.</p

Association of FGF-23 with aPWV in the whole population.

<p>Model 1 adjusted for age, sex (male/female), eGFR, current smoking (No/Yes), arterial hypertension (No/Yes), dyslipidaemia (No/Yes), BMI, TD1M (No/Yes) and FGF-23. Model 2 adjusted for covariates in model 1 and reflecting mineral metabolism (calcium, phosphate, PTH and 25(OH)D). Model 3 adjusted for covariates in model 2 and low-grade inflammation general score and ED score. 25(OH)D were additionally adjusted for seasonality.</p><p>Association of FGF-23 with aPWV in the whole population.</p