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Evaluation of a screening algorithm to detect cardiac amyloidosis in mild to severe aortic valve stenosis
Fabian Voß1, Elric Zweck2, Jean Marc Haurand2
1Division of Cardiology, Pulmonology and Vascular Medicine, Medical Faculty, Heinrich-Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany. Fabian.Voss@med.uni-duesseldorf.de.
Insights
Cardiac amyloidosis (CA) is underdiagnosed in aortic stenosis (AS) patients. A new screening algorithm identified a high prevalence of CA, particularly in mild to moderate AS, suggesting improved early diagnosis potential.
Area of Science:
- Cardiology
- Cardiovascular Imaging
- Cardiac Biomarkers
Background:
- Cardiac Amyloidosis (CA) is frequently underdiagnosed, especially in patients with conditions causing increased ventricular wall thickness like Aortic Stenosis (AS).
- The prevalence of CA across the spectrum of AS severity is not well-established, and validated diagnostic parameters for this specific population are lacking.
- This study introduces and prospectively evaluates a novel screening algorithm designed for CA detection in patients with mild to severe AS.
Background:
Cardiac Amyloidosis (CA) remains highly underdiagnosed, especially among patients with causes of increased ventricular wall thickness, such as aortic stenosis (AS). The prevalence of CA throughout the spectrum of mild to severe AS is unknown and specific validated diagnostic parameters for this population are lacking. Here, we propose and prospectively evaluate a screening algorithm for CA among patients with mild to severe AS.
Methods:
In this prospective, single-center study (NCT05010980), we included patients ≥ 65 years with mild to severe AS, an interventricular septum thickness > 11 mm, and at least one of the following criteria: Sokolow-Lyon-Index to left ventricular mass index ratio < 1.6 or stroke volume index < 35 ml/m2. Participants were prospectively screened for CA according to current guideline recommendations.
Results:
After screening 2126 patients of whom 187 were eligible, 57 participants were enrolled and completed the diagnostic work-up. Mean age was 83 ± 0.7 years and 71% were male. 30% of the participants had mild, 37% had moderate and 33% had severe AS, respectively. Overall 26% of participants were diagnosed with CA. The prevalence of CA was higher among patients with mild AS (41%) compared to participants with moderate (24%) or severe AS (16%, p = 0.01). Within this preselected patient population, troponin (AUC:0.9, p < 0.0001) and NT-proBNP (AUC:0.86, p < 0.0001) further improved discrimination of patients with and without CA.
Conclusion:
The prevalence of CA among AS patients fulfilling the preselected inclusion criteria was high, especially among those with mild to moderate AS. Implementing these criteria in clinical protocols could improve early diagnosis of CA.
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