Utility of cardiovascular implantable electronic device–derived patient activity to predict clinical outcomes

The role of cardiovascular implantable electronic device (CIED)–derived activity to predict implantable cardioverter-defibrillator (ICD) therapy or death is not known. We aimed to assess CIED-derived activity to predict clinical outcomes. In 1500 patients enrolled in MADIT-RIT, CIED-derived patient activity was acquired daily, then averaged for the first 30 days following randomization to predict inappropriate/appropriate therapy or death. Kaplan-Meier analysis and Cox proportional regression models were used to evaluate inappropriate/appropriate therapy, heart failure, or death by 30-day CIED-derived patient activity quintiles. There were 1463 patients with CIED activity data (98%). Patients in the highest quintile (Q5) of activity (more active) had the highest rate of inappropriate therapy, 21% at 2 years, as compared to 7%–11% in the other 4 quintiles (P < .001), a 1.75 times higher risk (95% confidence interval [CI]: 1.23–2.50, P = .002). However, patients in the lowest quintile of activity (Q1, 1 hour/day) had the highest risk of mortality, 15% in 2 years, as compared to Q2–3 (1–2 hours/day, 8%–7% mortality), and Q4–5 (>2 hours/day, 2%–3% mortality) (P < .001). Patients with the lowest level of activity (Q1) had a 2.02 times higher risk of mortality (95% CI: 1.21–3.38, P = .007), and they had an 82% higher risk of heart failure hospitalization (95% CI: 1.28–2.57, P = .001). High CIED-derived 30-day median patient activity predicted inappropriate therapy, while low patient activity predicted mortality and heart failure in ICD and cardiac resynchronization therapy with defibrillator patients enrolled in MADIT-RIT. Device-derived activity assessment could serve as a useful predictor of outcomes. [Display omitted]