Clinical Research Directory

Prognostic Role of AI-Echo

Sponsor: University of Calabria

Summary

Left atrial cardiomyopathy (LACM) is frequently underdiagnosed but plays a key role in increasing the risk of atrial fibrillation (AF) and thromboembolic events. While atrial strain is a validated marker of LACM, its measurement with conventional echocardiography can be time-consuming and less feasible in acute settings. The use of AI-assisted echocardiography (AI-echo) may help streamline image acquisition and analysis, offering faster and potentially more accurate assessment. This study aims to compare the time required for atrial strain analysis using AI-echo versus standard methods. It also explores how changes in strain parameters (LASr, LASct, LAScd) relate to the onset of AF and in-hospital adverse outcomes, adjusting for comorbidities and conventional echo variables. Main endpoints include time reduction with AI-echo and the association between strain changes and AF, complications, or mortality during hospitalization.

Official title: Evaluation of Artificial Intelligence-Assisted Echocardiography (AI-echo) in the Early Diagnosis and Prognostic Stratification of Left Atrial Cardiomyopathy (LACM) in Patients With Acute Cardiac Disease

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