Background: Heart failure is a leading cause of hospitalization and a significant medical burden in our society. Implantable medical devices are nowadays established therapies in heart failure patients that not only provide cardiac resynchronization therapy (CRT) and implantable cardioverter defibrillators (ICDs) therapy but are also able to continuously and remotely monitor diagnostic information of various physiologic parameters. The value of combining individual diagnostic variables to predict worsening of heart failure is still largely unclear but could eventually become a valuable tool towards a better heart failure management.
Methods: SELENE HF (Selection of potential predictors of worsening Heart Failure) is an observational, multicentre study designed to prospectively collect follow-up and home monitoring data trends from a population of individuals with ICDs with or without resynchronization therapy (CRT-D), to document heart failure hospitalizations and deaths and to correlate these events with Home Monitoring data in order to identify the combination with the greatest sensitivity and specificity in predicting heart failure events.The purpose of this study is to describe the design of the study focusing on the Heart Failure Predicting model and statistical approach that will be used to analyse the data.
Conclusion: The results of the SELENE HF study could help to select and define potential predictors of worsening heart failure in patients with remotely monitored ICD or CRT-D devices.
Trial registration: ClinicalTrials.gov Identifier NCT01836510.