NCT07009639

Prognostic Role of AI-Echo

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 45 (estimated)
• Sponsor: University of Calabria · Academic / Other
• Sex: All
• Age: 18 Years – 85 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Atrial Cardiomyopathy

Timeline

• Start date: 2025-07-01
• Primary completion: 2025-09-01
• Completion: 2025-11-30
• First posted: 2025-06-06
• Last updated: 2025-08-11

Locations

1 site across 1 country: Italy