Targeted screening for transthyretin cardiac amyloidosis in severe aortic stenosis: development and validation of a clinical risk score

Background

Patients undergoing transcatheter aortic valve implantation (TAVI) for severe aortic stenosis (AS) have a relatively high prevalence prevalence of Transthyretin cardiac amyloidosis (ATTR), yet optimal screening strategies have not been clearly established.

Purpose

To develop and validate an easily utilized risk score for predicting ATTR in patients with severe AS undergoing TAVI.

Methods

In the prospective multicentre GRECA-TAVI registry, 500 patients with severe AS scheduled for TAVI were screened for ATTR using technetium-99m–labelled DPD or PYP bone scintigraphy across 12 tertiary hospitals in Greece and Cyprus, between January 1 and December 31, 2024. Systematic collection of clinical, electrocardiographic and echocardiographic data was performed. An integer-based risk score derived from logistic regression was developed in a training cohort (n=350) and subsequently validated in a validation cohort (n=150). Model performance was assessed in terms of discrimination, calibration, and decision curve analysis.

Results

ATTR was diagnosed in 38 patients (7.7%). Older age, male sex, reduced left ventricular ejection fraction (LVEF), greater maximal wall thickness (MWT), higher prevalence of atrial fibrillation, and increased rates of intracardiac device implantation were more frequent among ATTR-CM patients. Five variables (age, sex, MWT, LVEF, and intracardiac device presence) formed the basis of an 8-point risk score. The score demonstrated good discrimination (AUC=0.75 in the training cohort and 0.76 in the validation cohort; Figure 1A).

At a score ≥4, the model identified 8 of 11 ATTR-CM cases in the validation cohort, while flagging 46 patients in total, achieving a sensitivity of 72.7% and a negative predictive value of 97.1% (Figure 1B). Using this threshold, ATTR-CM prevalence was approximately 16% among patients with a score ≥4, compared with 2.4% in those with a score <4. This cutoff captured 73% of ATTR-CM cases while limiting screening to 36% of the overall cohort (Figure 1C). Decision curve analysis demonstrated net clinical benefit across clinically relevant thresholds (5–20%) compared with both a guideline-recommended approach (MWT ≥12 mm) and a screen-all strategy (Figure 1D).

Conclusions

A simple bedside score derived from routinely available clinical variables can identify patients with severe AS at increased risk of ATTR-CM. Targeted screening based on this tool may improve diagnostic yield while optimizing resource utilization.Figure