Smartphone Data Reveals Early Signs of Rare Heart Disease

Smartphone and wearable data may detect idiopathic pulmonary arterial hypertension (IPAH) months before traditional diagnosis, according to a new pilot study. IPAH, a rare and fatal condition, causes progressive narrowing of lung arteries, often diagnosed too late due to vague symptoms like fatigue and breathlessness.

Researchers analyzed up to eight years of activity and heart rate data from 109 UK participants - including IPAH patients, disease controls, and healthy individuals. A machine learning classifier distinguished IPAH cases from controls with 87% accuracy (ROC AUC 0.87). When combined with app-collected questionnaire data, accuracy rose to 94% (ROC AUC 0.94).

External validation in a U.S. cohort showed more modest results (ROC AUC 0.74), highlighting population variability. Still, wearable metrics strongly correlated with the six-minute walk test, a key clinical measure of functional capacity.

The findings suggest digital health data could become a vital tool for remote risk stratification. However, researchers stress the need for larger, prospective trials to validate real-world use across diverse populations.