Background: Acute hyperglycemia predicts adverse outcomes in patients with acute myocardial infarction (AMI), but it has a major disadvantage because the association is diminished in patients with diabetes mellitus (DM). Recent studies introduced a more accurate predictor, the glycemic gap (the difference between admission blood glucose and the estimated average glucose), that could anticipate adverse outcomes in patients with diabetes with AMI. Aims: This study aimed to determine the association between glycemic gap and clinical outcome in diabetic patients presenting with AMI to a tertiary hospital in Bangladesh. Methods: Two hundred twenty diabetic patients hospitalized with AMI were included in this study from the Department of Cardiology of Chittagong Medical College Hospital from March 2023 to February 2024. Admission blood glucose and HbA1c were measured, and the glycemic gap was calculated. Patients were prospectively followed during their hospital stay to obtain data regarding major adverse cardiac events (MACEs). Results: The mean (±SD) age of the patients was 56.5 (±10.1) years and 63.6% of them were male. MACEs included in-hospital death, cardiac arrest, cardiogenic shock, arrhythmia and left ventricular failure were observed in 6.4%, 3.6%, 19.5%, 5.5%, and 30.5% of the patients, respectively. Ninety-nine (45%) patients had one or more MACEs. Median (IQR) glycemic gap values were 38.5 (31.9-47.3) and 71.0 (61.0-84.3) in patients without any MACEs and patients with one or more MACEs, respectively (p<0.001). Median (IQR) glycemic gap values were 90.6 (86.0-97.9) and 52.6 (36.1-69.3) in expired and survived patients, respectively (p<0.001). The area under the receiver operating characteristics curve (AUROC) for admission glycemic gap values to predict in-hospital mortality was 0.895[95% confidence interval (CI) 0.768-1.000, p<0.001] and with the best cut-off value of 80.16, glycemic gap had sensitivity and specificity of 92.9% and 89.8%, respectively.The Area Under ROC for admission glycemic gap values to predict MACEs was 0.926 (95% CI 0.874-0.958) and with the best cut-off value of 53.19, glycemic gap had a sensitivity and specificity of 94.9% and 84.3%, respectively. Glycemic gap was an independent predictor of MACEs [odds ratio (OR): 1.11, 95% CI 1.08-1.14, p <0.001] and in-hospital mortality (OR: 1.09, 95% CI 1.05-1.14, p <0.001). Conclusions: Elevated glycemic gap was significantly associated with an increased in-hospital mortality and other MACEs. So, glycemic gap can be used to assess the prognosis of hospitalized AMI patients with diabetes.
Read full abstract