AccurKardia has announced a new study demonstrating that its artificial intelligence (AI)-enabled electrocardiogram (ECG) technology, AK-AVS, can detect aortic stenosis years before patients require valve replacement and improve prediction of clinical outcomes.
The study was led by principal investigator Matthew Segar, an electrophysiology fellow at the Texas Heart Institute (Houston, USA) and published in the European Heart Journal–Digital Health.
The study evaluated AccurKardia’s AK-AVS AI model across both community-based populations and patients who underwent transcatheter aortic valve implantation (TAVI) at Baylor St Luke’s Medical Center (Houston, USA).
The study found that AK-AVS can detect aortic stenosis through routine ECGs up to 4.5 years before TAVI intervention, potentially enabling earlier detection, easier-to-access monitoring, and better timing of intervention.
The findings also demonstrated that patients who screened positive for aortic stenosis using AI-ECG but did not yet show disease on echocardiography—traditionally labeled as “false positives”—still demonstrated a 4.4-fold increased risk of future aortic stenosis hospitalisation during a median 6.2 years of follow-up. These results suggest the model may identify early electrical changes in the heart that occur before structural abnormalities are visible through conventional imaging.
Additionally, the study showed that AI-ECG trajectory patterns independently predict increased one-year mortality risk following TAVI, identifying patient risk that is not captured by widely used clinical risk scores such as the Society of Thoracic Surgeons (STS) and EuroSCORE models.
“This study demonstrates that AK-AVS could not only enable earlier detection of aortic stenosis, but it may also be a useful tool in surveillance and predicting outcomes,” said David Shavelle, chief of Cardiology for the MemorialCare Health System (Long Beach, USA).
Segar, added: “By detecting subtle electrical remodelling patterns and tracking how they evolve over time, this technology has the potential to transform how clinicians screen, monitor, and risk-stratify patients, ultimately helping physicians intervene earlier and improve outcomes in aortic stenosis.”
Because ECGs are widely available, inexpensive, and routinely performed in clinical practice, AI-enhanced ECG analysis may expand access to screening and risk assessment across broad patient populations, AccurKardia says in a press release.
Moin Hussaini, chief product officer for AccurKardia, said: “Our next step is to complete real-world pilots of AK-AVS to demonstrate its ability to identify undiagnosed aortic stenosis patients and inform their subsequent treatment.”
