From estimation to quantification: using left atrial reservoir strain to guide therapy in acute myocardial infarction

Background Accurate assessment of diastolic dysfunction in ST-segment elevation myocardial infarction (STEMI) is crucial for guiding treatment strategies, yet conventional echocardiographic parameters often have limited sensitivity for estimating left ventricular filling pressure (LVFP). Left atrial reservoir strain (LARS) has recently emerged as a promising non-invasive indicator. Purpose To evaluate the diagnostic accuracy of LARS for detecting elevated left ventricular end diastolic pressure (LVEDP) in STEMI patients after successful primary PCI, and to assess differences according to culprit vessel location. Methods This single-center observational cross-sectional study included 103 STEMI patients who underwent successful primary PCI. Invasive LVEDP was measured post-procedure, with elevated LVEDP defined as >18 mmHg. Comprehensive echocardiography with speckletracking analysis for LARS was performed within 24 hours. Patients were stratified by culprit artery (LAD vs. non-LAD). Correlation analysis, ROC curves, and multivariate regression were used to assess diagnostic performance. Results LARS showed a strong inverse correlation with LVEDP (r = –0.58, p < 0.001), outperforming E/e′ (r = 0.45). A LARS cutoff ≤22.5% identified elevated LVEDP with 78% sensitivity and 73% specificity (AUC = 0.79). Diagnostic accuracy varied by infarct location: LAD infarctions demonstrated excellent performance (AUC = 0.87; r = –0.71) with an optimal cutoff ≤23.0%, whereas non-LAD infarctions showed moderate accuracy (AUC = 0.70; r = –0.42). In multivariate analysis, LARS remained the strongest independent predictor of LVEDP (β = –0.45, p < 0.001). Crucially, left atrial function was more impaired in the LAD group, as shown by a significantly lower LARS (21.2% vs. 23.5%, p=0.008). Conclusion LARS is a superior non-invasive marker for estimating elevated LVEDP in STEMI patients, with significantly enhanced performance in LAD-related infarction due to a tight pathophysiological coupling, and more moderate in non-LAD infracts. Our proposed diagnostic matrix and location-stratified algorithm provide a practical framework to implement this evidence, moving from a one-size-fits-all approach to personalized hemodynamic assessment. By multi-parametric algorithm that integrates LARS with conventional parameters, we provide a roadmap for translating this advanced echocardiographic measure into confident, evidence-based clinical decision-making.