Assessment of Endothelial Dysfunction: The Role of Symmetrical Dimethylarginine and Proinflammatory Markers in Chronic Kidney Disease and Renal Transplant Recipients
Table 3
The results of ROC analysis for discriminating impaired from non-impaired FMD.
AUC (95% CI)
Std. error
Sensitivity %
Specificity %
AUC (95% CI)b
P
SDMA
0.689 (0.549–0.829)
0.071
81.8
58.3
0.686 (0.540–0.820)
0.007
hs-CRP
0.754 (0.602–0.905)
0.054
73.3
75.8
0.735 (0.628–0.840)
0.001
IL-6
0.699 (0.597–0.802)
0.052
72.3
52.6
0.690 (0.579–0.789)
0.002
SAA
0.605 (0.486–0.725)
0.061
76.7
51.4
0.093
0.593 (0.467–0.719)
0.064
69.2
34.5
0.174
Model: hs-CRP and SDMA
0.730 (0.582–0.878)
0.076
0.728 (0.592–0.855)
0.005
Model: hs-CRP and
0.671 (0.531–0.812)
0.072
0.639 (0.517–0.771)
0.025
Model: hs-CRP, SDMA, and
0.756 (0.623–0.888)
0.068
0.741 (0.616–0.859)
0.004
Model: IL-6 and SDMA
0.732 (0.614–0.851)
0.061
0.704 (0.593–0.813)
0.001
Model: IL-6 and
0.628 (0.507–0.749)
0.062
0.070
Model: IL-6, SDMA, and
0.724 (0.570–0.878)
0.079
0.715 (0.566–0.846)
0.003
Model: SDMA and
0.737 (0.598–0.876)
0.071
0.655 (0.533–0.778)
0.002
Data in parentheses are 95% confidence intervals (95% CIs). Sensitivity and specificity were calculated for optimal cutoff value. bThe AUC and 95% confidence intervals of the 1000 bootstrap samples.
