Viz.ai Data Suggests AI ECG Screening Could Identify HCM Years Earlier

Event summary

  • Viz.ai presented three studies at ACC.26 demonstrating the effectiveness of its Viz HCM AI-powered ECG analysis solution for detecting hypertrophic cardiomyopathy (HCM).
  • The studies suggest AI-ECG screening can identify previously undiagnosed HCM patients and those lost to follow-up, with one study identifying 11 new HCM diagnoses.
  • One study found that 13% of initially “false positive” AI-ECG results progressed to phenotypic HCM over an average of 2.74 years, prompting a suggestion for repeat echocardiography.
  • Viz.ai has accumulated 15 clinical abstracts supporting its Viz HCM solution, developed in collaboration with Bristol Myers Squibb.
  • The Viz HCM solution is the first FDA-cleared AI algorithm for detecting signs of HCM from a standard 12-lead ECG.

The big picture

The high rate of undiagnosed HCM (85%) represents a significant unmet need and a substantial opportunity for AI-driven diagnostic tools. Viz.ai’s partnership with Bristol Myers Squibb underscores the growing convergence of AI and pharmaceutical innovation in disease management. The demonstrated ability to identify patients earlier could lead to improved outcomes and reduced healthcare costs, but hinges on successful integration into existing clinical workflows and payer reimbursement models.

What we're watching

Workflow Integration
The impact of prospective AI-ECG implementation on clinical workflows and practice patterns remains to be seen, and will be a key factor in adoption rates.
Pre-Positive Cohort
The identification of a “pre-positive” cohort warrants further investigation to determine the optimal timing and frequency of follow-up echocardiography.
Reimbursement Expansion
Viz.ai’s existing CMS reimbursement for AI will likely be a model for broader adoption, but the pace of expansion for AI-driven diagnostic tools will depend on payer acceptance and clinical validation.

Related topics

Medical Devices