A classifier trained on pre-diagnostic wearable activity and heart rate data distinguished individuals with idiopathic pulmonary arterial hypertension from controls with an ROC AUC of 0.87, improving to 0.94 with questionnaire input.
Observational (n=182)
Yes
Does smartphone and wearable data improve the early detection and classification of idiopathic pulmonary arterial hypertension in at-risk individuals?
Digital health tools utilizing smartphone and wearable data can accurately distinguish patients with idiopathic pulmonary arterial hypertension from controls, potentially supporting earlier detection.
Effect estimate: ROC AUC 0.87
Abstract Idiopathic pulmonary arterial hypertension (IPAH) is a progressive, life-limiting condition often diagnosed late due to non-specific symptoms and requirement of invasive right heart catheterisation. This pilot study explores the feasibility of using real-world physical activity data from wearable devices and a smartphone app (My Heart Counts) to aid earlier detection. We analysed up to eight years of retrospective data from 109 UK participants, including patients with IPAH, disease controls, and healthy individuals. A classifier trained on pre-diagnostic activity and heart rate, distinguished individuals with IPAH from healthy and disease controls with an ROC AUC of 0.87, improving to 0.94 with in-app questionnaire input. Validation in a matched US cohort yielded an ROC AUC of 0.74. Wearable-derived metrics correlated with clinical 6MWD supporting their potential to complement traditional risk assessment. These pilot findings suggest that digital health tools may support earlier detection and remote monitoring of IPAH warranting larger scale studies.
Delgado-SanMartin et al. (Wed,) conducted a observational in Idiopathic pulmonary arterial hypertension (IPAH) (n=182). Smartphone app (My Heart Counts) and wearable device (Apple Watch) vs. Healthy individuals and disease controls was evaluated on Classification of IPAH versus controls using pre-diagnostic watch activity and heart rate data (ROC AUC 0.87). A classifier trained on pre-diagnostic wearable activity and heart rate data distinguished individuals with idiopathic pulmonary arterial hypertension from controls with an ROC AUC of 0.87, improving to 0.94 with questionnaire input.