AI-assisted echocardiography to predict outcomes in left atrial cardiomyopathy
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
This will try whether AI-assisted echocardiography speeds up atrial strain measurements and whether those strain changes help predict atrial fibrillation and in-hospital complications in adults in a cardiac care unit.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 45 (estimated) |
| Ages | 18 Years to 85 Years |
| Sex | All |
| Sponsor | University of Calabria Academic / other |
| Locations | 1 site (Cosenza) |
| Trial ID | NCT07009639 on ClinicalTrials.gov |
What this trial studies
This observational, single-center study will compare the time needed to obtain atrial strain measurements using AI-assisted echocardiography versus conventional methods in patients hospitalized in the cardiac care unit. Investigators will record LASr, LASct, and LAScd parameters and track the onset of atrial fibrillation and in-hospital adverse outcomes, adjusting analyses for comorbidities and standard echocardiographic variables. The primary endpoints are reduction in analysis time with AI-echo and the association between strain changes and AF, complications, or mortality during hospitalization. Adult patients (18–85) admitted for acute cardiac conditions who can give written consent will be enrolled at the Annunziata Hospital (Cosenza, Italy).
Who should consider this trial
Good fit: Adults aged 18–85 hospitalized in the coronary/cardiac care unit for acute cardiac problems and able to provide written informed consent are the ideal candidates.
Not a fit: Patients who are severely hemodynamically unstable, have a very poor echocardiographic window, cannot continue or refuse consent, or are not admitted to the CCU are unlikely to benefit from participation.
Why it matters
Potential benefit: If successful, AI-echo could provide faster and more consistent atrial strain readings that help clinicians identify patients at higher risk of AF or complications sooner.
How similar studies have performed: Atrial strain is an established marker of left atrial disease and prior work shows AI can speed echocardiographic analysis, but applying AI-echo for in-hospital prognostic prediction is still relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
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.
Where this trial is running
Cosenza
- "Annunziata" Hospital — Cosenza, Italy (Recruiting)
Study contacts
- Study coordinator: Antonio Curcio, Medicine
- Email: antonio.curcio.cardio@unical.it
- Phone: +390984681877
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.