A Wearable Infrared Sensor for Detecting Non-ST Segment Elevation Acute Coronary Syndromes

Non-ST-segment elevation acute coronary syndrome (NSTE-ACS) is conventionally diagnosed using electrocardiography and serial blood biomarker measurements. We investigated a non-invasive, bloodless, and electrode-free diagnostic strategy using a wrist-worn infrared spectrophotometric biosensor (Infrasensor). In a prospective, multicenter study of 595 patients with suspected NSTE-ACS enrolled across 13 sites in two countries, participants were stratified into five analytical cohorts. With 200 multi-ethnic controls and a leave-one-cohort-out external validation, a machine learning model detected high-grade coronary obstruction with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% CI: 0.84-0.90), 90% specificity, and 84% positive predictive value-surpassing standard risk scores. A secondary model predicted freedom from NSTE-ACS and adverse outcomes over 30 days with an AUC of 0.89 (95% CI: 0.87-0.92), 99% sensitivity, and 96% negative predictive value. These findings demonstrate the potential of the Infrasensor as a rapid, scalable point-of-care tool for early risk stratification in NSTE-ACS.