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Background Elevated plasma glucose levels on admission (APG) are very common in patients with acute coronary syndrome (ACS) and can be the first indication of diabetes mellitus. Objective To provide insight into the prevalence of previously undiagnosed diabetes and to compare different methods of diagnosing diabetes in patients with ACS. Methods Patients with ACS with elevated APG who participated in the BIOMArCS 2 glucose trial underwent an oral glucose tolerance test (OGTT) prior to discharge. 130 patients were included who underwent metabolic assessment. Of these, 109 had an OGTT and 13 patients had pre-existing diabetes. Results The OGTT results were categorised as (previously) undiagnosed diabetes in 35% of patients (fasting plasma glucose (FPG) ≥7.0 mmol/l or 2-h post-load glucose ≥11.1 mmol/l) and impaired glucose metabolism in 44% (FPG 6.1-6.9 mmol/l or post-load glucose 7.8-11.0 mmol/l), so only 21% had a normal glucose metabolism. Undiagnosed diabetes could not be adequately predicted with APG, FPG or HbA1c (area under the ROC curve 0.61, 0.75 and 0.72, respectively). Patients with abnormal glucose metabolism were significantly older, had higher admission HbA1c values, a higher Killip classification and more often had a prior stroke than patients with normal glucose metabolism. Conclusion 79% of hyperglycaemic patients with ACS were found to have abnormal glucose metabolism. As APG, HbA1c and FPG had a low sensitivity to detect undiagnosed diabetes, an OGTT appears to be the best test to assess the presence of previously undiagnosed diabetes or impaired glucose metabolism in hyperglycaemic patients with ACS. [ABSTRACT FROM AUTHOR]

Objective: Admission plasma glucose (APG) is a biomarker that predicts mortality in myocardial infarction (MI) patients. Therefore, APG may improve risk stratification based on the GRACE risk score. Methods: We collected data on baseline characteristics and long-term (median 55 months) outcome of 550 MI patients who entered our hospital in 2003 and 2006. We determined the GRACE risk score at admission for each patient, which was entered in a logistic regression model, together with APG, to evaluate their prognostic value for 6-month and 5-year mortality. Results: Patients with APG ≥7.8 mmol/l had a higher mortality than those with APG levels <7.8 mmol/l; 6 months: 13.7 versus 3.6%, p value <0.001; 5 years: 20.4 versus 11.1%, p value 0.003. After adjustment for the GRACE risk score variables, APG appeared a significant predictor of 6-month and 5-year mortality, adjusted OR 1.17 (1.06-1.29) and 1.12 (1.03-1.22). The combination of the GRACE risk score and APG increased the model's performance (discrimination C-index 0.87 vs. 0.85), although the difference was not significant (p = 0.095). Combining the GRACE risk score and APG reclassified 12.9% of the patients, but the net reclassification improvement was nonsignificant (p = 0.146). Conclusion: APG is a predictor of 6-month and 5-year mortality, each mmol/l increase in APG being associated with a mortality increase of 17 and 12%, respectively, independent of the GRACE risk score. However, adding APG to the GRACE model did not result in significantly improved clinical risk stratification. Copyright © 2012 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The article discusses the Biomarker Study to Identify the Acute Risk of a Coronary Syndrome also known as the BIOMArCS study which investigates the relation between cardiovascular biomarkers and ischemic cardiovascular events after acute coronary syndrome. Several cardiovascular biomarkers were measured including troponin, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and high-sensitivity C-reactive protein (hs-CRP).

The article focuses on a randomized trial BIOMArCS-2 Glucose which was conducted to evaluate the effect of using intensive glucose control (IGC) in myocardial infarction (MI). Topics discussed include no association between use of IGC in hyperglycemic MI patients and improved outcomes, lowering blood glucose in hyperglycemic causes excess mortality and risk of higher mortality during long term follow-up.