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Glycated hemoglobin measurement and prediction of cardiovascular disease

Di, Angelantonio, Gao, Pei, Khan, Hassan, Butterworth, Adam, Wormser, David, Kaptoge, Stephen, Kondapally, Seshasai, Thompson, Alexander, Sarwar, Nadeem, Willeit, Peter, Ridker, Paul, Barr, Elizabeth L. M., Khaw, Kay, Psaty, Bruce, Brenner, Hermann, Balkau, Beverley, Dekker, Jacqueline, Lawlor, Debbie and Daimon, Makoto (2014). Glycated hemoglobin measurement and prediction of cardiovascular disease. JAMA: Journal of the American Medical Association,311(12):1225-1233.

Document type: Journal Article
Citation counts: Altmetric Score Altmetric Score is 122
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IRMA ID 84473306xPUB11
Title Glycated hemoglobin measurement and prediction of cardiovascular disease
Author Di, Angelantonio
Gao, Pei
Khan, Hassan
Butterworth, Adam
Wormser, David
Kaptoge, Stephen
Kondapally, Seshasai
Thompson, Alexander
Sarwar, Nadeem
Willeit, Peter
Ridker, Paul
Barr, Elizabeth L. M.
Khaw, Kay
Psaty, Bruce
Brenner, Hermann
Balkau, Beverley
Dekker, Jacqueline
Lawlor, Debbie
Daimon, Makoto
Journal Name JAMA: Journal of the American Medical Association
Publication Date 2014
Volume Number 311
Issue Number 12
ISSN 0098-7484   (check CDU catalogue  open catalogue search in new window)
Scopus ID 2-s2.0-84896675182
Start Page 1225
End Page 1233
Total Pages 9
Place of Publication United States
Publisher American Medical Association
HERDC Category C1 - Journal Article (DIISR)
Abstract Importance
The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain.

Objective
To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk.

Design, Setting, and Participants
Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment.

Main Outcomes and Measures
Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk.

Results
During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels.

Conclusions and Relevance

In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

DOI http://dx.doi.org/10.1001/jama.2014.1873   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
 
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