Prevalence of cardiac amyloidosis in screening studies: a systematic review and meta-analysis
Alberto Aimo, Vincenzo Castiglione, Giorgia Panichella, Marianna Fontana, Michele Emdin, Giuseppe VergaroAbstract
Background
Cardiac amyloidosis (CA) is an under-recognized cause of heart failure. Its prevalence in screening studies, and the extent to which selective confirmatory testing affects prevalence estimates, remain uncertain across clinical settings.
Methods
We systematically searched PubMed/MEDLINE and EMBASE up to 10 August 2025. Two reviewers independently screened studies and extracted data. We grouped studies by clinical setting and combined prevalence estimates using random-effects meta-analysis. For each study, we calculated CA prevalence in 1) the whole enrolled cohort and 2) the subgroup who underwent confirmatory testing.
Results
Eighty-three studies were included. Pooled CA prevalence (whole cohort; tested subgroup) was highest in left ventricular hypertrophy/hypertrophic cardiomyopathy [LVH/HCM] (15.1%; 35.4%), followed by heart failure [HF]—mainly HF with preserved or mildly reduced ejection fraction (HFpEF/HFmrEF)—(12.6%; 13.6%) and aortic stenosis [AS] (9.6%; 11.6%). Orthopedic cohorts were lower overall (4.1%) but higher in tested subgroups (12.4%); “no specific red flags” showed 1.8% vs. 7.8%; non-cardiac bone scintigraphy was 0.49% in both denominators. Across settings, transthyretin CA predominated over light-chain CA. Several studies approached systematic screening in the general elderly; however, they were few and still applied referral criteria to second-level examinations.
Conclusion
This meta-analysis shows that CA is relatively frequent in HFpEF/HFmrEF, severe AS, and LVH/HCM. To obtain reliable population estimates, future studies should test either all eligible participants or a predefined random sample, rather than only those with suspected disease. In clinical practice, screening strategies should clearly define which higher-risk individuals are referred for second-level tests, balancing diagnostic yield with feasibility.