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

Area of Science:

• Cardiology
• Biomedical Engineering
• Medical Devices

Background:

• The predictive role of cardiovascular implantable electronic device (CIED)-derived activity for implantable cardioverter-defibrillator (ICD) therapy or mortality remains unclear.
• Assessing patient activity via CIEDs could offer insights into clinical outcomes.

Purpose of the Study:

• To evaluate the association between CIED-derived patient activity and clinical outcomes, specifically inappropriate/appropriate ICD therapy, heart failure, and death.
• To determine if early post-randomization activity levels can predict future adverse events.

Main Methods:

• Analysis of daily CIED-derived patient activity data averaged over the first 30 days post-randomization in 1463 patients from the MADIT-RIT trial.
• Kaplan-Meier analysis and Cox proportional regression models were employed to assess outcomes across activity quintiles.

Main Results:

• Patients in the highest activity quintile (Q5) showed a significantly higher rate of inappropriate therapy (21% at 2 years) compared to lower quintiles (7%-11%), with a 1.75 times higher risk.
• Conversely, patients in the lowest activity quintile (Q1, 1 hour/day) exhibited the highest mortality risk (15% at 2 years) and an 82% higher risk of heart failure hospitalization.
• Low activity (Q1) was associated with a 2.02 times higher risk of mortality.

Conclusions:

• CIED-derived activity is a valuable predictor of clinical outcomes in patients with ICDs and cardiac resynchronization therapy defibrillators.
• High activity levels correlate with an increased risk of inappropriate therapy, whereas low activity levels are predictive of mortality and heart failure.
• Routine monitoring of CIED-derived activity may enhance risk stratification and patient management.