Figure 3 | Scientific Reports

Figure 3

From: Gender differences in fasting and postprandial metabolic traits predictive of subclinical atherosclerosis in an asymptomatic Chinese population

Figure 3

Summary of Logistic Regression and gender stratified ROC analysis results—A clinical tool for predicting risk of subclinical atherosclerosis in males (a) and females (b). ROC curve cut points with classification parameters, model coefficients, odds ratios and p values are shown. The ROC curve reflects prediction accuracy of multivariable model for presence of subclinical atherosclerosis. (a) Logistic regression atherosclerosis linear predictor for males: y = − 0.8997 − 0.1238∙Cholesterol iAUC120min + 0.3903∙Framingham Score − 0.0315∙Diff Insulin Conc. t30–t45 min − 0.6704∙Diff TNFa Conc. t60–t240 min (b) Logistic regression atherosclerosis linear predictor for females: y = 24.0507 − 0.0259∙C-peptide iAUC120min + 2.5158∙Diff Triglyceride Conc. t60-t240min – 3.2593∙Glucose Conc. t10 min. Predicted probability of atherosclerosis:〖p = e〗^y/(1 + e^y). TN, True negative; FN, False negative; FP, False positive; TP, True positive; PPV, Positive predictive value; NPV, Negative predictive value; CI, Confidence interval; AUC, Area under curve; TNFa, Tumor necrosis factor alpha; iAUC, incremental area under curve; PAI-1, Plasminogen activator inhibitor-1.

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