Abstract
Unplanned admissions for worsening heart failure (WHF) are the largest resource cost in heart failure (HF) management. Despite advances in pharmacological agents and interventional therapy, HF remains a global epidemic. One crucial-and costly-gap in HF management is the inability to obtain objective information to identify and quantify congestion and personalize treatment plans to effectively manage WHF events without resorting to expensive, invasive methods. Although the causes of WHF are varied and complex, the universal effect of HF decompensation is the significant decline in quality of life due to symptoms of hypervolemic congestion and the resultant reduction in cardiac output, which can be quantified via increased pulmonary venous congestion due to high intracardiac filling pressures. Accessible and reliable markers of congestion could more precisely quantify the severity of WHF events and stabilize patients earlier by interrupting and reversing this process with timely introduction or modification of evidence-based treatments. Pulmonary artery and cardiac pressure sensing tools have gained evidential credence and increased clinical uptake in recent years for the prevention and treatment of WHF, as studies of implantable hemodynamic devices have iteratively and reliably demonstrated substantial reductions in WHF events. Recent advances in sensing technologies have ranged from single-parameter invasive pulmonary artery monitors to completely non-invasive multi-parameter devices incorporating multi-sensor concept technologies aided by machine learning or artificial intelligence, although many remain investigational. This review aims to evaluate the potential for novel pulmonary artery and cardiac pressure sensing technology to reshape the management of WHF from within the hospitalized and ambulatory care environments.