AI-Enhanced ECG Predicts Hypertension, Related Risks

METHODOLOGY:

• Researchers conducted a development and external validation prognostic cohort study in a secondary care setting to identify individuals at risk for incident hypertension.
• They developed AIRE-HTN, which was trained on a derivation cohort from the Beth Israel Deaconess Medical Center in Boston, involving 1,163,401 ECGs from 189,539 patients (mean age, 57.7 years; 52.1% women; 64.5% White individuals).
• External validation was conducted on 65,610 ECGs from a UK-based volunteer cohort, drawn from an equal number of patients (mean age, 65.4 years; 51.5% women; 96.3% White individuals).
• Incident hypertension was evaluated in 19,423 individuals without hypertension from the medical center cohort and in 35,806 individuals without hypertension from the UK cohort.

TAKEAWAY:

• AIRE-HTN predicted incident hypertension with a C-index of 0.70 (95% CI, 0.69-0.71) in both the cohorts. Those in the quartile with the highest AIRE-HTN scores had a fourfold increased risk for incident hypertension (P < .001).
• The model’s predictive accuracy was maintained in individuals without left ventricular hypertrophy and those with normal ECGs and baseline blood pressure, indicating its robustness.
• The model was significantly additive to traditional clinical markers, with a continuous net reclassification index of 0.44 for the medical center cohort and 0.32 for the UK cohort.
• AIRE-HTN was an independent predictor of cardiovascular death (hazard ratio per 1-SD increase in score [HR], 2.24), heart failure (HR, 2.60), myocardial infarction (HR, 3.13), ischemic stroke (HR, 1.23), and chronic kidney disease (HR, 1.89) in outpatients from the medical center cohort (all P < .001), with largely consistent findings in the UK cohort.

Results of exploratory and phenotypic analyses suggest the biological plausibility of these findings. Enhanced predictability could influence surveillance programs and primordial prevention.

 

https://www.medscape.com/viewarticle/ai-enhanced-ecg-predicts-hypertension-related-risks-2025a10000h5