Development of a Method to Risk Stratify Patients With Heart Failure for 30-Day Readmission Using Implantable Device Diagnostics

Abstract

The aim of the present study was to evaluate whether diagnostic data collected after a heart failure (HF) hospitalization can identify patients with HF at risk of early readmission. The diagnostic data from cardiac resynchronization therapy defibrillator (CRT-D) devices can identify outpatient HF patients at risk of future HF events. In the present retrospective analysis of 4 studies, we identified patients with CRT-D devices, with a HF admission, and 30-day postdischarge follow-up data. The evaluation of the diagnostic data for impedance, atrial fibrillation, ventricular heart rate during atrial fibrillation, loss of CRT-D pacing, night heart rate, and heart rate variability was modeled to simulate a review of the first 7 days after discharge on the seventh day. Using a combined score created from the device parameters that were significant univariate predictors of 30-day HF readmission, 3 risk groups were created. A Cox proportional hazards model adjusting for age, gender, New York Heart Association class, and length of stay during the index hospitalization was used to compare the groups. The study cohort of 166 patients experienced a total of 254 HF hospitalizations, with 34 readmissions within 30 days. Daily impedance, high atrial fibrillation burden with poor rate control (>90 beat/min) or reduced CRT-D pacing (<90% pacing), and night heart rate >80 beats/min were significant univariate predictors of 30-day HF readmission. Patients in the "high"-risk group for the combined diagnostic had a significantly greater risk (hazard ratio 25.4, 95% confidence interval 3.6 to 179.0, p = 0.001) compared to the "low"-risk group for 30-day readmission for HF. In conclusion, device-derived HF diagnostic criteria evaluated 7 days after discharge identified patients at significantly greater risk of a HF event within 30 days after discharge.