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Left atrioventricular coupling Index as a parameter of diastolic dysfunction in type 2 diabetes mellitus

Oct 2026 · European Heart Journal · 0 citations

Abstract

Diabetes mellitus (DM), particularly type 2, is a major risk factor for cardiovascular disease and is associated with early myocardial involvement, frequently manifesting as diastolic dysfunction before the development of overt systolic impairment. Left atrial (LA) dysfunction and altered atrial–ventricular interaction are increasingly recognized as important contributors to diabetic cardiomyopathy. This study investigates the predictive role of the Left Atrioventricular Coupling Index (LACI) in assessing cardiac dysfunction in T2DM patients and its correlation with other echocardiographic parameters. A cross-sectional case-control study was conducted on 52 adults with T2DM and 50 age-matched healthy controls. Echocardiographic parameters, including LACI, LA strain, E/e’, and LV ejection fraction (LVEF), were analyzed. LACI was significantly higher in diabetics (22.5 ± 4.5%) compared to controls (15.5 ± 3.4%, p<0.001). LACI showed a strong correlation with E/e’ (r=0.49) and LA strain (r=-0.78), indicating its association with diastolic dysfunction. Receiver Operating Characteristic (ROC) curve analysis demonstrated an optimal LACI cutoff of ≥21.15%, with 100% sensitivity and 86% specificity (AUC = 0.927), indicating excellent diagnostic performance. These findings highlight LACI as a highly sensitive and specific marker for detecting subclinical diastolic dysfunction in diabetic patients. LACI reflects early alterations in atrial–ventricular interaction and is strongly associated with echocardiographic markers of diastolic dysfunction in type 2 diabetes mellitus. Its integrative nature and feasibility support its potential role as a screening parameter for early myocardial involvement in this population. Further longitudinal studies are needed to validate its prognostic significance and explore its applicability in routine echocardiographic evaluation.ROC curve analysis for LACIPearson correlation heatmap

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