Anumana Receives First-of-its-Kind ECG-AI Algorithm to Detect Cardiac Amyloidosis Using Standard 12-Lead ECG

Anumana, Inc. has received U.S. Food and Drug Administration (FDA) clearance for its ECG-AI® algorithm designed to detect cardiac amyloidosis (CA) using standard 12-lead electrocardiograms. 

The software-as-a-medical-device (SaMD) is the first and only FDA-cleared solution for this indication.

Cardiac amyloidosis is a life-threatening condition caused by abnormal protein deposits in the heart that can lead to heart failure. 

It is frequently underdiagnosed due to non-specific symptoms that overlap with other cardiac disorders. 

The newly cleared algorithm aims to support earlier identification at the point of care by analysing routine ECG data and flagging patients who may require further diagnostic evaluation.

The ECG-AI model, initially developed at Mayo Clinic and subsequently validated in a multi-centre study involving over 25,000 patients across four U.S. health systems, demonstrated 78.9% sensitivity and 91.2% specificity in detecting cardiac amyloidosis in symptomatic populations.

The system identifies subtle waveform patterns not easily recognised through standard human interpretation and integrates into existing clinical workflows without additional testing requirements. 

It builds on Anumana’s existing portfolio of FDA-cleared ECG-AI tools, which include algorithms for low ejection fraction and pulmonary hypertension.

According to the company, the clearance supports its broader strategy of expanding ECG-based AI applications to improve early detection of underdiagnosed cardiovascular conditions and enhance clinical decision-making.