Predictors of mortality by an artificial intelligence enhanced electrocardiogram model for cardiac amyloidosis.

ABSTRACT:

Aims

We aim to determine if our previously validated, diagnostic artificial intelligence (AI) electrocardiogram (ECG) model is prognostic for survival among patients with cardiac amyloidosis (CA).

Methods

A total of 2533 patients with CA (1834 with light chain amyloidosis (AL), 530 with wild-type transthyretin amyloid protein (ATTRwt) and 169 with hereditary transthyretin amyloid (ATTRv)] were included. An amyloid AI ECG (A2E) score was calculated for each patient reflecting the likelihood of CA. CA stage was calculated using the European modification of the Mayo 2004 criteria for AL and Mayo stage for transthyretin amyloid (ATTR). Risk of death was modelled using Cox proportional hazards, and Kaplan-Meier was used to estimate survival.

Results

Median age of the cohor

SUBMITTER: Amadio JM 

PROVIDER: S-EPMC11769637 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature