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RESEARCH PRODUCT

P4570Prognostic interest of HbA1c and plasma glucose assessment on one-year mortality in non-diabetic patients after acute myocardial infarction

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Abstract Background The usefulness of the combined assessment of HbA1c and plasma glucose (PG) in acute myocardial infarction (AMI) in nondiabetic patients remains unclear. Purpose In a large observational study, we aimed to identify the prognostic values of these biomarkers regarding one-year all-cause mortality in nondiabetic patients after AMI. Methods From the “obseRvatoire des Infarctus de Côte d'Or” (RICO) survey database, we included all consecutive nondiabetic patients with AMI (n=6617) from May 2001 to December 2016. Exclusion criteria were: admission known or unknown diabetes, in-hospital death. The primary endpoint was all-cause one-year mortality. The secondary endpoints were: MACE, infarct size, LVEF<40% and GRACE risk score. Cut off levels (high/low) were determined by ROC curve analysis for the prediction of one-year death (HbA1c 5.9% and PG 7.3mmol/L) to set up 4 groups: low HbA1c/low glucose (n=3158), low HbA1c/high glucose (n=1264), high HbA1c/low glucose (n=1378) and high HbA1c/high glucose (n=817). Results Elevation of PG was associated with elevated rate of LVEF<40%, STEMI, anterior wall location, DFG<60mL/min/m2 and higher troponin Ic pic (all p<0.001); HbA1c>5.9% was associated with elevated rate of CRP>3mg/L (p<0.001); High HbA1C and high PG together were associated with higher rate of MACE (p<0.001). By multivariate logistic regression analysis, elevated admission PG remained a strong predictor of one-year all-cause (OR (95% CI): 1.64 (1.31–2.05)) mortality and cardiovascular mortality (OR (95% CI): 1.75 (1.33–2.31)), beyond GRACE score (OR (95% CI): 1.03 (1.03–1.04)), as well as elevated HbA1c (OR (95% CI): 1.43 (1.15–1.78) and OR (95% CI): 1.83 (1.39–2.41) respectively). Conclusions Admission PG and HbA1c had strong independent predictive value regarding one-year all-cause mortality in our nondiabetic patients with AMI. These biomarkers could be useful to identify the most-at-risk patients after AMI in order to reduce residual risk in this target population. Acknowledgement/Funding University Hospital Center Dijon Bourgogne, France