Strategies to detect abnormal glucose metabolism in people at high risk of cardiovascular disease from the ORIGIN (Outcome Reduction with Initial Glargine Intervention) trial population.
ABSTRACT To investigate whether the combination of HbA1c and fasting plasma glucose (FPG) can be used for the diagnosis of diabetes and impaired glucose tolerance (IGT) in people at high risk of cardiovascular disease (CVD).
A cross-sectional study was performed on 2907 people at high risk of cardiovascular events but without a previous diagnosis of diabetes. Optimal cut-off points and the diagnostic potential of FPG, HbA1c, and their combination were determined.
The sensitivity of the usually applied FPG cut-off point of 7.0 mmol/L to diagnose diabetes mellitus was low (59.0%). Receiver operating characteristic (ROC) curve analysis indicated that the optimal cut-off points for the diagnosis of diabetes using FPG and HbA1c were 6.4 mmol/L (sensitivity 75.7%; specificity 77.5%; likelihood ratio 3.37) and 5.9% (41 mmol/mol; sensitivity 68.7%; specificity 67.1%; likelihood ratio 2.09), respectively. To diagnose IGT, the optimal cut-off points for FPG and HbA1c were 6.1 mmol/L (sensitivity 57.1%; specificity 57.9%) and 5.7% (39 mmol/mol; sensitivity 63.8%; specificity 60.3%), respectively. For diabetes, combining cut-off points for FPG and HbA1c identified four categories with likelihood ratios ranging from 5.59 to 0.21, and post-test probabilities between 69.3% and 7.8%. For IGT, likelihood ratios varied between 2.05 and 0.56, whereas post-test probabilities ranged from 84.0% to 58.8%.
Using FPG alone results in the underdiagnosis of glucometabolic abnormalities in people at high risk of CVD. Using an algorithm with both HbA1c and FPG improves the detection of diabetes, but not IGT, and could be easily implemented in patient care.
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ABSTRACT: Obesity and insulin resistance are risk factors for cardiovascular diseases. Whether insulin-sensitive obese individuals are at higher risk for cardiovascular diseases is still debated. We aim to investigate whether insulin-sensitive obesity associates with prevalent cardiovascular diseases and 10-year coronary heart disease (CHD) risk. At the baseline of the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) study, 211,641 participants aged 40years or older were recruited from 25 communities across the China mainland, in 2011 to 2012. Participants were categorized by insulin-sensitive/resistant and general/abdominal obese status. Cardiovascular diseases included CHD, stroke, and myocardial infarction. Framingham risk score (FRS) was calculated according to National Cholesterol Education Program-Adult Treatment Panel III and FRS greater than 20% or cardiovascular diseases were identified as high risk for 10-year CHD. Controlling for potential confounders, compared with insulin-sensitive normal weight individuals, insulin-sensitive general obese individuals had increased risks for prevalent cardiovascular diseases (men: OR, 2.55, 95% CI, 2.04-3.18; women: 1.73, 1.45-2.06) and 10-year Framingham risk for CHD (men: 2.26, 1.86-2.76; women: 1.73, 1.46-2.06). Compared with insulin-sensitive normal waist subgroup, insulin-sensitive abdominal obesity was associated with higher risks for prevalent cardiovascular diseases (men: 1.32, 1.20-1.46; women: 1.36, 1.27-1.47) and 10-year Framingham risk for CHD (men, 1.34, 1.23-1.45; women, 1.37, 1.27-1.47). Both general and abdominal obesity were associated with elevated prevalent cardiovascular diseases and 10-year CHD risk, regardless of the presence or absence of insulin resistance.International journal of cardiology 01/2014; · 6.18 Impact Factor
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ABSTRACT: Using high-normal levels of hemoglobin A1C (Abnormal-A1C) or fasting plasma glucose (FPG) (Abnormal-FPG) for diabetes screening is expected to improve the ability to detect persons with or at high risk of diabetes. We assessed the diagnostic and predictive capacity for diabetes of Abnormal-A1C and Abnormal-FPG and compared these between the combined use of the two measures and the single use of either measurement. We analyzed 31 eligible cross-sectional or cohort studies that assessed diagnostic or predictive ability, respectively, by using lower A1C and FPG cutoff values than recommended by current diabetes criteria. Positive and negative likelihood ratios (LR + and LR-) were calculated to assess the ability to confirm or exclude diabetes, respectively, based on a bivariate random-effects model. With both Abnormal-A1C and Abnormal-FPG, the pooled LR + was above 4 for diagnosing diabetes and above 3 for predicting diabetes. However, the pooled LR- for predicting diabetes was higher with Abnormal-A1C (0.48) and Abnormal-FPG (0.49) in comparison with that for diagnosing diabetes (0.27, Abnormal-A1C; 0.28, Abnormal-FPG). In 8 studies that assessed the predictive ability of the combination of A1C and FPG, using either Abnormal-A1C or Abnormal-FPG could lower LR- to 0.17 from 0.43 for only Abnormal-A1C and from 0.38 for only Abnormal-FPG. Accordingly, LR + was also lowered to 2.37 from 3.36 for only Abnormal-A1C and from 3.84 for only-Abnormal-FPG. In conclusion, the use of the two blood glucose tests had insufficient capacity to identify subjects at high risk for diabetes but had considerable capacity to identify undiagnosed diabetes. This article is protected by copyright. All rights reserved.Diabetes/Metabolism Research and Reviews 08/2013; · 3.59 Impact Factor