Screening Algorithm for Early Detection of Occult Cardiac Amyloidosis

Evaluation of a Screening Algorithm for Early Detection of Occult Cardiac Amyloidosis in Subjects at Risk

Early diagnosis of cardiac amyloidosis (CA) is crucial because of the poor overall survival, high mortality and the need for early therapy including new treatment possibilities for transthyretin amyloidosis. Previously considered a rare condition, CA is being demonstrated to account for up to 17 % of heart failure with preserved ejection fraction cases as well as up to 16 % of Patients with severe aortic stenosis, undergoing surgical of transcatheter aortic valve replacement. It seems that CA is being underdiagnosed as the data of post-mortem studies demonstrate that at least 25% of elderly individuals have histologic evidence of amyloid deposits. Other common conditions with increased afterload such as hypertensive or hypertrophic heart disease that mimic echocardiographic features or clinical symptoms may be the reason of postponed recognition of CA. Furthermore, the lack of definitive biomarkers makes the diagnosis even more challenging. However, it has been shown that some clinical, laboratory and echocardiographic findings, so called "red flags", may indicate occult CA. A deeper and constructive analysis of the findings and establishment of prediction criteria could possibly lead to improvement of early CA recognition and survival in subjects at risk. We aim to prospectively perform a systematic screening for CA in individuals at risk based on predefined selection criteria. Our aim is to evaluate if specific criteria would lead to increased detection of CA and in this case, to define major and minor diagnostic criteria.

The study aims to perform a prospective screening and detect occult CA in subjects at risk with aortic valve stenosis, undergoing either transcatheter or surgical aortic valve replacement. The study has two main objectives. Firstly, we aim to determine the real prevalence of CA according to the targeted "red flags" analysis and secondly, we aim to establish an algorithm for early detection of CA.

Inclusion Criteria:

• Fulfillment of following four criteria: 1) Severe aortic stenosis. 2) Age > 65 years for male and >70 years for female. 3) Increased left ventricular wall thickness ≥14 mm. 4) Blood pressure ≤ 140/90 mmHg and at least 1 major or ≥ 2 minor criteria.

Major criteria:

1. Carpal tunnel syndrom
2. Non-traumatic rupture of the biceps tendon
3. NT-proBNP > 1000 pg/ml
4. hs Troponin value above the 99th percentile without dynamic changes (≤ 20%)

Minor criteria:

1. Diastolic dysfunction (at least grade 2, E' < 10 cm/s)
2. Sinus bradycardia/AV block/pacemaker
3. Atrial fibrillation

Exclusion Criteria:

• Known cardiac amyloidosis (ATTR or AL)
• Unable to provide written informed consent
• Refusal to provide written informed consent
• Contraindications for study investigations