Artificial Intelligence–based Model Successful at Predicting Hypertension

An electrocardiography (ECG)–based artificial intelligence risk estimator can predict the development of hypertension, according to a recent study published in JAMA Cardiology.

Hypertension stands as a significant cause of global morbidity and mortality. The researchers noted that Artificial intelligence–enhanced electrocardiography (AI-ECG) has been shown to identify a broad spectrum of subclinical disease and may be useful for predicting incident hypertension.

In this development and external validation prognostic study of a AI-ECG risk estimator (AIRE) to predict incident hypertension (AIRE-HTN) model, researchers analyzed 1, 163,401 ECGs from 189,539 patients between 2014 and 2022. The primary end point of interest was the prediction of incident hypertension.

According to the findings, the AIRE-HTN score was an independent predictor of cardiovascular death ([HR] = per standard deviation, 2.24; 95% CI, 1.67-3.00) and stratified risk 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), beyond traditional risk factors.

“Results suggest that AIRE-HTN, an AI-ECG model, can predict incident hypertension and identify patients at risk of hypertension-related adverse events, beyond conventional clinical risk factors,” the researchers concluded.