Medscape January 9, 2025
TOPLINE:
An artificial intelligence–ECG risk estimation model designed to predict incident hypertension (AIRE-HTN) identifies cases and stratifies the risk for adverse outcomes in addition to traditional markers.
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...
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