Prevalence of clinical manifistetions of transthyretin amyloid cardiomyopathy among patients with heart failure with preserved ejection fraction in the Russian Federation: the TETRAMER study

Aim. To assess the prevalence of clinical manifestations of transthyretin amyloid cardiomyopathy (ATTR-CM), as well as to analyze the demographic and clinical characteristics of patients, including paraclinical investigations conducted in this sample, in patients with heart failure with preserved ejection fraction (HFpEF) in Russia according to the real-world study.

Material and methods. As part of the retrospective part, we analyzed the data of patients with HFpEF previously included in a prospective observational multicenter registry study of heart failure in research centers with ability to diagnose ATTR-CM. Symptoms and signs associated with a high probability of ATTR-CM ("red flags") were recorded based on anamnestic and paraclinical data. Based on interim analysis (n=1770, 29,5% of the planned number of patients), we decided to stop the study and not conduct a prospective phase that involved verifying the diagnosis of ATTRCM in patients with a high risk of its presence.

Results. The mean age of the included patients was 69,7±10,0 years (women, 55,8% (n=988)). Left ventricular (LV) posterior wall thickness (PWT) was measured in 1704 (96,3%) patients. It exceeded 12 mm in 287 (16,8%) cases. Possible signs of ATTR-CM were detected in 1702 (96,2%) participants. Three or more possible signs of ATTR-CM were detected in 1262 (71,3%) patients in the general population. Among patients with available LV PWT measurements, 219 (76,3%) participants with thickness >12 mm had ≥3 possible signs of ATTR-CM. Using the risk calculator, only 117 (7,33%) patients had a high probability of this disease.

Conclusion. More than two thirds of patients with HFpEF have several clinical signs associated with a high risk of ATTR-CM. About 7% of patients selected using the risk calculator may be primary candidates for examination to verify the diagnosis. However, determining the optimal algorithm for diagnosing ATTRCM requires further study.

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