Blood Glucose Control Measurements Improve CVD Risk Prediction in People with Diabetics
In a publication in the Archives of Internal Medicine, researchers from Brigham and Women’s Hospital reported that measuring HbA1c (hemoglobulin1c) levels of diabetes patients can improve the predictability of CVD (cardiovascular disease) risk. According to the authors, CVD risk is catapulted by diabetes and recent studies reveal that the risk varies considerably amongst diabetics. They wrote:
“Simulated cost-benefit analyses have suggested that this variability in CVD risk could provide an opportunity for tailored preventive therapy in diabetic patients.”
Nina P. Paynter, Ph.D. and team embarked upon determining the effect of monitoring HbA1clevels in predicting cardiovascular events. An HbA1c test provides an estimate of the average blood glucose levels over the past 8 to 13 weeks and is an indicator of whether a patient’s diabetes is under control or not.
Data gathered by researchers from the Women’s Health Study as well as the Physician’s Health Study II revealed that out of 24,674 females and 11,280 males, 685 females and 563 males had diabetes at baseline. Participants provided all details of their medical history by completing questionnaires. HbA1c, C-reactive protein, and cholesterol levels were evaluated using baseline blood samples.
Males and females were followed-up for new CVD incidences for an average of 11.8 years and 10.2 years, respectively.
The following observations were made during the follow-up period:
• Amongst females, 685 participants exhibited 125 cardiovascular events compared to 665 females out of 24,674 without diabetes.
• Amongst males, 563 participants exhibited 170 cardiovascular events compared to 1,382 out of 11.280 without diabetes.
Compared to the blanket prediction that diabetes are at an all time high risk of CVD events, incorporating an HbA1c model improved CVD prediction, as said by researchers. This was noteworthy among females.
In this study, the risk model employed by researchers demonstrated that compared to 24.5% of diabetic males, 71.9% of female counterparts had less than 20% risk of CVD over a ten-year period.
However, with risk models involving the term HbA1c, CVD risk prediction improved considerably for women and more discreetly for men.
The authors state:
“Using a yes/no term for diabetes instead of HbA1c also improved prediction over classification as high risk in both men and women. In women, however, HbA1c further improved prediction over the yes/no term. We found that in these large population-based cohorts of both men and women, presence of diabetes alone did not confer a 10-year risk of CVD higher than 20 percent, and measurement of HbA1c level in diabetic subjects improved risk prediction compared with classification as cardiovascular risk equivalent.
The difference in CVD risk between men and women can be partly attributed to higher CVD risk with age and delayed risk in females, said the authors. They added that their findings need to be substantiated by further studies. Nonetheless, the researchers concluded:
“Our findings suggest that the improvement in CVD risk prediction, and possibly calibration, obtained with adding HbA1c levels is highest in lower-risk populations.”
Commentary: Cardiovascular Risk Stratification, HbA1c, and the Tempo of Translation
Cardiovascular disease guidelines including Adult Treatment Panel III (ATP III) guidelines are soon to be updated explained Dr. Mark J. Pletcher, M.P.H., from the University of California, San Francisco.
“One specific guideline refinement up for consideration this year is the approach to CVD risk stratification in patients with diabetes.”
Under the current ATP III guidelines, diabetes is seen as a “Coronary heart disease (CHD) risk equivalent.” Diabetes patients may be subject to reasonably aggressive goals as well as treatment thresholds for decreasing cholesterol levels. Dr. Fletcher said:
“The article by Paynter and colleagues, which includes the HbA1c level as well as other standard risk factors, appears to improve discrimination and may lead to “more accurate classification of individuals into risk categories.”
He added that stronger results would have been obtained from a study involving patients whose diabetes was not well controlled.
Dr. Fletcher wrote:
“If it had not included revascularizations and strokes, as these were not considered when the current ATP III CHD risk-prediction equation was developed and calibrated; and if the model had included a diabetes indicator variable as well as the HbA1c measurement…It is not enough to know whether discrimination or reclassification improves with the additional measurement; harm from the new measurement/strategy (both direct and indirect) must be considered and weighed against a realistic estimate of the expected health benefits.”