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Table 2 Logistic regression models considering HPR as endpoint

From: Incremental role of glycaemic variability over HbA1c in identifying type 2 diabetic patients with high platelet reactivity undergoing percutaneous coronary intervention

 

p-value

OR (95% CI)

Model 1 (pseudoR2: 0.499, p < 0.001)

 HbA1c

0.012

7.25 (1.55–33.86)

Model 2 (pseudoR2: 0.757, p < 0.0001)

 HbA1c

0.019

13.21 (1.52–114.19)

 MAGE

0.034

1.094 (1.007–1.188)

Model 3 (pseudoR2: 0.618, p < 0.0001)

 HbA1c

0.018

9.13 (1.46–56.79)

 CV

0.071

1.22 (0.98–1.53)

  1. HPR high platelet reactivity, Hb1Ac glycated hemoglobin, MAGE mean amplitude glucose excursions, CV coefficient of variation
  2. In the multivariate analysis (hierarchical enter method) HPR was entered in the model as dependent variable and as independent variables were included only the variables with p < 0.10 at the bivariate regression analysis: HbA1c, MAGE and CV. Excluded variables: fasting blood glucose, BMI, age, gender, weight, left ventricle ejection fraction, clopidogrel bolus (600 mg), chronic clopidogrel therapy, haemoglobin, haematocrit, platelet count number, white blood cells, total cholesterol, HDL, LDL, triglycerides and all the other glycaemic variability indexes (glycaemic average, SD, CONGA1, CONGA2, CONGA4, MAGE UP, MAGE DOWN); *p < 0.05
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Cardiovascular Diabetology

ISSN: 1475-2840