Remote Patient Care of Patients with Heart Failure: A Focused Review on the HeartLogic-System

Heart failure (HF) represents a growing clinical and socioeconomic burden worldwide, placing increasing pressure on health care systems in both high- and low-resource settings. Remote patient care (RPC), encompassing telemonitoring and other digitally enabled strategies, has emerged as a promising adjunct to conventional follow-up by enabling continuous physiological assessment and early detection of clinical deterioration. Such proactive surveillance facilitates timely therapeutic adjustments and may improve patients' outcomes. A broad range of monitoring approaches is currently available or under development, including patient-directed home measurements, wearable technologies, and sensor-based solutions integrated into therapeutic cardiac implantable electronic devices (CIEDs). Among these, the HeartLogic multisensory algorithm offers a pragmatic and scalable solution, leveraging data from existing CIEDs without the need for additional procedures. It is a multiparametric, implant-based algorithm that detects early signs of HF decompensation by integrating sensor data, including heart sounds, intrathoracic impedance, respiratory rate, heart rate, and patient activity. Growing evidence supports its clinical use. DANLOGIC-HF (Danish Pragmatic Randomized Trial to Evaluate the Effect of HeartLogic-Guided Management on Heart Failure Outcomes) is the first randomized controlled trial designed to provide robust outcome data about whether HeartLogic-guided management reduces HF-related events. In this article, we discuss the current evidence for HeartLogic, as well as ongoing and planned clinical trials, with particular emphasis on the pragmatic randomized controlled trial DANLOGIC-HF (Danish Pragmatic Randomized Trial to Evaluate the Effect of HeartLogic-Guided Management on Heart Failure).