ABSTRACT
This study aimed to determine the impact of dysglycemia on myocardial injury and cardiac dysfunction in acute myocardial infarctions (AMIs). From 2005 to 2016, a total of 1,593 patients with AMIs who underwent percutaneous coronary intervention were enrolled. The patients were classified into five groups according to the admission glucose level: ≤80, 81 to 140, 141 to 200, 201 to 260, and ≥261 mg/dL. The clinical and echocardiographic parameters and 30-day mortality were analyzed. The peak troponin I and white blood cell levels had a positive linear relationship to the admission glucose level. The left ventricular ejection fraction had an inverted U-shape trend, and the E/E' ratio was U-shaped based on euglycemia. The 30-day mortality also increased as the admission glucose increased, and the cut-off value for predicting the mortality was 202.5 mg/dL. Dysglycemia, especially hyperglycemia, appears to be associated with myocardial injury and could be another adjunctive parameter for predicting mortality in patients with AMIs.
ABSTRACT
This study aimed to determine the impact of dysglycemia on myocardial injury and cardiac dysfunction in acute myocardial infarctions (AMIs). From 2005 to 2016, a total of 1,593 patients with AMIs who underwent percutaneous coronary intervention were enrolled. The patients were classified into five groups according to the admission glucose level: ≤80, 81 to 140, 141 to 200, 201 to 260, and ≥261 mg/dL. The clinical and echocardiographic parameters and 30-day mortality were analyzed. The peak troponin I and white blood cell levels had a positive linear relationship to the admission glucose level. The left ventricular ejection fraction had an inverted U-shape trend, and the E/E' ratio was U-shaped based on euglycemia. The 30-day mortality also increased as the admission glucose increased, and the cut-off value for predicting the mortality was 202.5 mg/dL. Dysglycemia, especially hyperglycemia, appears to be associated with myocardial injury and could be another adjunctive parameter for predicting mortality in patients with AMIs.