Artificial intelligence-based echocardiographic assessment for monitoring disease progression in transthyretin cardiac amyloidosis.

ABSTRACT:

Aims

In transthyretin amyloid cardiomyopathy (ATTR-CM), reduced stroke volume (SV) portends a poor prognosis. Artificial intelligence (AI) enables rapid, standardized assessment of left ventricular outflow tract velocity-time integral (LVOT-VTI), which is a reliable surrogate for SV. We investigated longitudinal changes in AI-derived LVOT-VTI as outcome predictors in ATTR-CM.

Methods and results

Consecutive patients with ATTR-CM underwent baseline and 12 ± 1 month transthoracic echocardiography between 2007 and 2021. Scans were processed by an AI platform for fully automated measurements including LVOT-VTI. Changes in echocardiographic variables were related to all-cause mortality in a landmark analysis using multivariable Cox models adjusting for clinical covariates (age, s

SUBMITTER: Venneri L 

PROVIDER: S-EPMC12803646 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature