Blood glucose measure appears to provide little benefit in predicting risk of CVD

March 25, 2014

In a study that included nearly 300,000 adults without a known history of diabetes or cardiovascular disease (CVD), adding information about glycated hemoglobin (HbA1c), a measure of longer-term blood sugar control, to conventional CVD risk factors like smoking and cholesterol was associated with little improvement in the prediction of CVD risk, according to a study in the March 26 issue of JAMA.

Because higher glucose levels have been associated with higher CVD incidence, it has been proposed that information on might improve doctors' ability to predict who will develop CVD, according to background information in the article.

Emanuele Di Angelantonio, M.D., of the University of Cambridge, United Kingdom, and colleagues with the Emerging Risk Factors Collaboration, conducted an analysis of data available from 73 studies involving 294,998 participants to determine whether adding information on HbA1c levels to information about conventional is associated with improvements in the prediction of CVD risk. Predicted 10-year risk categories were classified as low (<5 percent), intermediate (5 percent to <7.5 percent), and high (≥ 7.5 percent).

Among the primary findings of the researchers, adding information on levels of HbA1c to conventional CVD was associated with only slight improvement in risk discrimination (how well a statistical model can separate individuals who do and do not go on to develop CVD). In addition, they found that adding information on HbA1c did not improve the accuracy of probability predictors for patients with and without CVD.

"Contrary to recommendations in some guidelines, the current analysis of individual-participant data in almost 300,000 people without known diabetes and CVD at baseline indicates that measurement of HbA1c is not associated with clinically meaningful improvement in assessment of CVD risk," the authors write.

Explore further: Lipid-related markers addition linked with slight improvement in cardiovascular disease prediction

More information: DOI: 10.1001/jama.2014.1873

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