Prognostic Role of AI-Echo

University of Calabria

Status: Enrolling

Conditions: Atrial Cardiomyopathy

Study type: Observational

Funder types: Other

Identifiers

NCT07009639

58/2025

Details and patient eligibility

About

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.

Enrollment: 45 estimated patients

Sex: All

Ages: 18 to 85 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Age between 18 and 85 years.
2. Hospitalization in CCU for acute cardiac pathology (e.g. acute coronary syndrome, acute or exacerbated heart failure, malignant arrhythmias, etc.).
3. Ability to provide written informed consent.

Exclusion criteria

1. Severe hemodynamic instability, history to contraindicate the execution of the echocardiographic examination.
2. Severely inadequate echocardiographic window that precludes atrial or ventricular morpho-functional assessment.
3. Inability to continue the study for clinical reasons, logistics or patient refusal.