Hemoglobin A1C and Prevention of Atherosclerotic CVD
What is the effect of glycated hemoglobin (HbA1C) measurements on the prediction of risk for cardiovascular disease (CVD) in the context of other CVD risk factors?
The authors developed a linear regression model for expected HbA1C using sex, race/ethnicity, and other traditional CV risk factors in the 2011-2012 National Health and Nutrition Examination Surveys (NHANES) sample. The population was limited to 2000 nonpregnant individuals ages 40-79 years. After establishing the expected distribution of HbA1C, the authors then combined pretest 10-year risk for atherosclerotic CVD (ASCVD) and expected HbA1C distribution to yield a single post-test risk for each HbA1C category (<5.7%, 5.7% to <6.5%, and ≥6.5%).
Age, sex, race/ethnicity, and traditional CV risk factors were significant predictors of HbA1C. Having an HbA1C of <5.7% reduced post-test risk by 0.4%-2.0%; having an HbA1C of ≥6.5% increased post-test risk by 1.0%-2.5%.
The incorporation of HbA1C into a model that includes traditional CV risk factors has a modest effect on the prediction of risk for ASCVD.
This is an interesting study that aims to investigate whether objective levels of glycemia (as measured by HbA1C) may help predict risk for CVD in individuals without diabetes mellitus. The Pooled Cohort Risk Equations do incorporate a clinical diagnosis of diabetes mellitus (but do not include levels of glycemia). The incorporation of HbA1C into a model with traditional CV risk factors had a modest effect. The authors posit that the post-test risk increase from having an HbA1C ≥6.5% ‘approximates the risk increase from being 5 years older.’ Further studies should establish the clinical importance of this increase in risk and more fully analyze the cost-effectiveness of HbA1C testing in the primary prevention of ASCVD.
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