Key result
Glycemic gap outperforms admission glucose for predicting MACE with superior discriminative ability.
Why the study?
Admission hyperglycemia in diabetic patients with ACS may reflect acute stress or chronic glycemic control, but admission glucose alone does not account for baseline glycemia. The glycemic gap, combining acute and chronic glucose measures, may better predict clinical outcomes in this population.
Does the glycemic gap predict in-hospital major adverse cardiac events better than admission random blood sugar in diabetic patients with acute coronary syndromes?
Cohort (n=110)
No
Does the glycemic gap predict in-hospital major adverse cardiac events better than admission random blood sugar in diabetic patients with acute coronary syndromes?
The glycemic gap is a reliable and superior predictor of in-hospital MACE and mortality compared to admission blood glucose alone in diabetic patients with ACS.
Answers are grounded in this paper and cite their sources.
Glycemic gap may refine MACE prediction in diabetic ACS beyond admission glucose; hypothesis-generating and requires prospective validation before practice change.
Background: Admission hyperglycemia occurs in 25%–50% of patients with acute coronary syndromes (ACS) and may be stress-induced or reflect underlying abnormal glucose metabolism. Stress-induced hyperglycemia causes myocardial injury through oxidative stress, inflammation, reperfusion injury, and postinfarction remodeling. In diabetic patients, admission glucose alone fails to account for baseline glycemic control. The A1c-derived average glucose (ADAG), calculated using the formula (28.7 × Glycated hemoglobin [HbA1c] −46.7), reflects chronic glycaemia. The glycemic gap, defined as the difference between admission glucose and ADAG, incorporates both acute and chronic glycemic status and may therefore better predict outcomes. Aims: To evaluate the association between glycemic gap and clinical outcomes in diabetic patients with ACS and to compare its prognostic value with admission hyperglycemia. Materials and Methods: This prospective study included 110 diabetic patients admitted with ACS at a tertiary care hospital. Electrocardiography, echocardiography, and HbA1c estimation were performed. Global registry of acute coronary events score and Killip class were calculated. ADAG and glycemic gap were derived and correlated with in-hospital outcomes. Results: Major adverse cardiac events (MACE) occurred in 26.4% of patients, with an in-hospital mortality of 13.6%. Glycemic gap showed a significant association with MACE ( P = 3.2 × 10 −6 ). Receiver operating characteristic analysis identified a glycemic gap cutoff of 22 mg/dL for predicting MACE. Glycemic gap demonstrated superior predictive ability compared to admission random blood sugar (AUC 0.876 vs. 0.757). Conclusion: Glycemic gap is a reliable predictor of MACE and mortality in diabetic patients with ACS and is superior to admission blood glucose alone.
No takes yet. Share an insight, caveat, or question.
Dixit et al. (2026) conducted a cohort in Acute Coronary Syndromes in Diabetes (n=110). Glycemic gap vs. Admission random blood sugar was evaluated on Major adverse cardiac events (MACE) (AUC 0.876, p=3.2 × 10^-6). Glycemic gap was significantly associated with MACE (P=3.2x10^-6) and demonstrated superior predictive ability compared to admission random blood sugar (AUC 0.876 vs. 0.757).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: