A NOVEL artificial intelligence (AI)-enhanced electrocardiography (ECG) model, AIRE-HTN, has demonstrated significant potential in predicting the development of hypertension and stratifying patients at risk for related adverse events.
Hypertension remains a major contributor to global morbidity and mortality. Early identification and intervention are critical to mitigating associated risks. In this study, researchers developed and validated the AIRE-HTN algorithm to predict incident hypertension and stratify patients for cardiovascular and renal complications. The algorithm was trained on 1,163,401 ECGs from 189,539 patients at Beth Israel Deaconess Medical Center (BIDMC) and externally validated on 65,610 ECGs from the UK Biobank (UKB).
Using a residual convolutional neural network architecture with a discrete-time survival loss function, AIRE-HTN achieved a concordance index (C index) of 0.70 (95% CI, 0.69–0.71) in both BIDMC and UKB cohorts. Importantly, the model maintained performance in individuals without left ventricular hypertrophy or ECG abnormalities. Beyond hypertension prediction, the AIRE-HTN score independently predicted cardiovascular death (hazard ratio [HR], 2.24; 95% CI, 1.67–3.00) and stratified risks for heart failure (HR, 2.60; 95% CI, 2.22–3.04), myocardial infarction (HR, 3.13; 95% CI, 2.55–3.83), ischemic stroke (HR, 1.23; 95% CI, 1.11–1.37), and chronic kidney disease (HR, 1.89; 95% CI, 1.68–2.12).
The findings suggest that integrating AI-driven tools like AIRE-HTN into clinical practice may enhance hypertension screening and risk stratification beyond traditional methods. This could lead to earlier interventions and improved outcomes for high-risk patients. Future studies should focus on evaluating the model’s real-world impact in diverse populations and healthcare settings. The incorporation of such AI models could redefine preventive strategies, improving the early detection and management of hypertension-associated complications.
Katrina Thornber, EMJ
Reference
Sau A et al. Artificial Intelligence–enhanced electrocardiography for prediction of incident hypertension. JAMA Cardiol. 2025;DOI:10.1001/jamacardio.2024.4796.
