Abstract 4147355: Tracking Mood Phenotypes in TIA and Ischemic Stroke Patients Using Smartphone Sensors: Preliminary Results from a Real-World Data Pilot Study

Background: Although no tests are currently available to predict post-stroke depression (PSD), a risk factor for diminished quality of life and stroke-related death, emerging evidence suggests that ischemic stroke (IS) may induce behavioral changes by damaging connections throughout the brain rather than via localized injury. Hypothesis: We sought to determine if active (surveys) and passive (accelerometer, GPS, and other sensors) smartphone data could quantify exploratory behavioral proxies of PSD. Methods: Thirty-four adults with a recent IS (n = 12) or transient ischemic attack (TIA) (n = 22) diagnosis were followed for 3 months. Participants used the Beiwe app to complete a weekly Patient Health Questionnaire-8 (PHQ-8) survey and were evaluated every 30 days with the Montgomery-Asberg Depression Rating Scale (MADRS). Results: Preliminary analysis of app survey compliance was adequate (86%), and the quantity of data collected was greater for Android than iOS phones. PHQ-8 indicated depression (moderate or severe) in 20% of participants. MADRS highly correlated with the most recent PHQ-8 ( r = 0.92, 95% CI (0.19, 0.99), P = 0.028). Several exploratory passive physical activity and social measures showed statistically significant change over time and/or associations with PHQ-8 and MADRS. Conclusion: Low-burden smartphone data holds promise for developing novel IS and TIA outcome measures as well as identifying patients most at risk of PSD.