Research Paper Volume 12, Issue 19 pp 19440—19454

Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome

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Nomogram to estimate individual ACS probability. Each predictor variable characteristic has a corresponding point value based on its position on the top point scale and contribution to the model. The probability of ACS for each subject is calculated by summing the points for each variable to obtain a total point value that corresponds to a probability of ACS from the scale presented on the bottom line. The variable data, including the relative expression of CCR7 and CXCR5, gender, age, smoking, drinking, BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), serum glucose, TC, TG, high-density lipoprotein cholesterol (HDL-C), LDL-C, apolipoprotein (Apo)A1, ApoB and defined the sores as follows: smoking and/or drinking: yes = 2, no = 1; male = 1; female = 2. The predictive accuracy of the risk model was assessed by discrimination measured by C-statistic and calibration evaluated by Hosmer-Lemeshow χ2 statistic. The discriminatory ability of the model was quantified using the area under the receiver operating characteristic curve (AUC). The discrimination accuracy of the model was 0.841 (95% CI, 0.809–0.871). At an optimal cutoff value, the sensitivity and specificity were 64.0% and 90.9%, respectively. *P < 0.05.