Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients (MultiSENSE Study)
Status: Completed in 2015
Heart failure (HF) involves costly hospitalizations with adverse impact on patient outcomes. The aim of this study was to develop and validate a device-based diagnostic algorithm and alert (HeartLogic™) to predict heart failure events (HFE).
- Sensitivity of 70% (95% confidence interval: 55.4% to 82.1%)
- Unexplained alert rate of 1.47 per patient-year (95% confidence interval: 1.32 to 1.65)
- The median lead time prior to HFE was 34.0 days (interquartile range: 19.0 to 66.3 days)
- International, multicenter, nonrandomized
- 900+ patients were followed for up to 1 year
- Heart Failure Events (HFE) were independently adjudicated to include events where primary cause was worsening HF and patient admission included an overnight stay or intravenous medications.
- Sensor data included heart rate, accelerometer-based heart sounds, respiration rate, relative tidal volume, activity, and intrathoracic impedance.
- Algorithm development combined key feature trends into a composite index and associated alert using HFE and sensor data from 500 patients in Development Set.
- Performance was evaluated against HFE and sensor data in sequestered Test Set patients. Two co-primary endpoints included:
- Sensitivity to detect HFE >40%
- Unexplained alert rate <2.0 per patient-year
- Age 18 or above
- Currently implanted with a COGNIS CRT-D system
- NYHA Class II, III, IV within the last 6 months
HeartLogic™ index and alert mechanisms are investigational and not available for sale.