April 24, 2026 – A novel detection algorithm spotted moderate-to-severe aortic stenosis (AS) with a sensitivity of 90.5% of all patients and 100% of African American patients.
Researchers presented the late-breaking data at the Society for Cardiovascular Angiography & Interventions (SCAI) 2026 Scientific Sessions & Canadian Association of Interventional Cardiology/Association Canadienne de cardiologie d’intervention (CAIC-ACCI) Summit in Montreal.
AS is a common, progressive heart valve disease that, if left untreated, can result in death within two years in half of patients with severe symptomatic cases. Since AS symptoms like fatigue, shortness of breath, and dizziness are often confused with normal signs of aging, timely screening and diagnosis are needed to refer patients for treatment, slow disease progression, and prevent mortality. However, older Black Americans face lower rates of AS diagnosis yet a higher mortality risk, underscoring the need for improved monitoring in this population.
The Recognition & Evaluation of Aortic Stenosis to Create Health (REACH) trial is a prospective, non-randomized, unblinded study conducted across three sites in the U.S. Researchers divided them into two cohorts: one group with moderate-to-severe AS and one group without it, confirmed by echocardiography. Researchers used the Acumen IQ cuff technology (Edwards Lifesciences), an air-filled cuff placed around the finger to continuously measure the patient’s pulse and pressure in the arteries. Using the data from the Acumen cuff, clinicians ran the ASI algorithm to screen for moderate-to-severe AS cases and monitored its sensitivity and specificity optimization. Sensitivity measures a diagnostic test's ability to correctly identify people with a disease, while specificity is the ability of a test to correctly identify individuals who do not have a disease.
Of the total cohort of 346 patients, 47.1% (163) were male, and 26.9% (93) were African American. When looking at sensitivity, results found that the algorithm correctly detected 90.5% of moderate-to-severe AS cases in the overall patient population (Confidence Interval (CI): [84.6, 96.4]), and 100% of the time in African American patients. As for specificity, the ASI algorithm correctly detected 70.9% of healthy individuals in the overall patient population (CI: [65-76.8]), and 73% of the time in African American patients (CI: 63.2, 82.8]). Findings suggest the ASI algorithm had excellent performance for screening purposes.
“The ASI algorithm, paired with the Acumen cuff, performed consistently well across age, gender, and racial groups, showing no signs of bias and demonstrating strong performance in screening for moderate-to-severe aortic stenosis,” said Pedro Engel Gonzalez, MD, cardiologist at Henry Ford Health in Detroit, Michigan.
“Our findings give us hope for communities that are more likely to experience limitations to care. Something as simple as a finger cuff and an algorithm can help improve early diagnoses and get patients the care that they need.”
Future studies are warranted to uncover how this detection technology might be used to assist with AS referral in order to facilitate treatment in communities known to experience inequities.
April 14, 2026 
