CONGRESS ABSTRACT

INTRODUCTION:  Heart failure (HF) is a chronic condition with high morbidity and mortality, affecting over 64 million people worldwide. Aging populations and comorbidities increase reliance on informal caregivers (ICs), who play a vital role in HF management. Effective HF care should prioritize the dyad, addressing perspective differences, fostering collaboration, and improving physical and psychological health. Even telemedicine interventions, which have significantly increased in recent years, should focus on the HF dyad approach rather than on individual members.  OBJECTIVE:  To map and classify telemedicine interventions for HF dyads.  METHODS:  This scoping review adheres to JBI methodology, with searches conducted in MEDLINE  (PubMed), CINHAL, Web of Science and grey literature. Two reviewers will independently screen studies using predefined criteria. Data extraction will follow the JBI Unified Management, Assessment, and Review Information System. The review includes studies focus on HF dyads (a patient with HF and an IC) regardless of clinical status or relationship type. Eligible studies must evaluate telemedicine interventions aimed at disease management, behavioural changes, and dyadic health. Interventions should be home-based, delivered remotely without healthcare professionals' physical presence, and unrestricted by location.  RESULTS:  A database search on October 26, 2024, yielded 962 references. An updated search will follow in December 2024. Findings will be presented through tabular charting and descriptive statistics, including counts, frequencies, and content analyses, aligning results with the review objectives.  DISCUSSION AND EXPECTED FINDINGS:  Mapping telemedicine interventions for HF dyads will optimize their delivery. The variety of technological solutions may complicate selecting suitable options. A systematic mapping aligned with the framework will support patient and caregiver management as a cohesive unit, improving collaborative care and outcomes.  FUNDING AKNOWLEDGEMENTS:  This abstract is part of the NODES project that received funding from the MUR – M4C2 1.5 of the EU-funded PNRR – NextGenerationEU (Grant agreement no. ECS000036).