Abstract
Heart failure (HF) hospitalisations due to decompensation are associated with shorter life expectancy and lower quality of life. These hospitalisations pose a significant burden on the patients, doctors and healthcare resources. Early detection of an upcoming episode of decompensation may facilitate timely optimisation of the ambulatory medical treatment and thereby prevent heart-failure-related hospitalisations. The HeartLogicTM algorithm combines data from five sensors of cardiac implantable electronic devices into a cumulative index value. It has been developed for early detection of fluid retention in heart failure patients. This review aims to provide an overview of the current literature and experience with the HeartLogicTM algorithm, illustrate how the index can be implemented in daily clinical practice and discuss ongoing studies and potential future developments of interest.
Highlights
Multisensory Algorithm, Heart failure is a syndrome that is defined by the European Society of Cardiology as “a clinical syndrome characterized by typical symptoms that may be accompanied by signs caused by a structural and/or functional cardiac abnormality, resulting in a reduced cardiac output and/or elevated intracardiac pressures at rest or during stress” [1]
The aim of this review is to provide an overview of the current knowledge and literature on the HeartLogicTM algorithm
We demonstrate that the HeartLogicTM algorithm is validated for early detection of fluid retention and highlight ongoing and future studies regarding the clinical implementation of the algorithm
Summary
Multisensory Algorithm, Heart failure is a syndrome that is defined by the European Society of Cardiology as “a clinical syndrome characterized by typical symptoms (e.g., breathlessness, ankle swelling and fatigue) that may be accompanied by signs (e.g., elevated jugular venous pressure, pulmonary crackles and peripheral edema) caused by a structural and/or functional cardiac abnormality, resulting in a reduced cardiac output and/or elevated intracardiac pressures at rest or during stress” [1] It results in substantial mortality, morbidity and worsening of clinical status, often leading to hospitalisations because of fluid retention [2,3,4]. Various tele- and remote monitoring initiatives have gained interest for their promise in detecting an upcoming episode of decompensation before patients experience clinical symptoms This may facilitate timely adjustment of ambulatory medical treatment and prevent heart-failure-related hospitalisations [14]. We demonstrate that the HeartLogicTM algorithm is validated for early detection of fluid retention and highlight ongoing and future studies regarding the clinical implementation of the algorithm
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