Abstract
CardioMEMS, a remote pulmonary artery pressure monitoring system, provides waveform patterns for the ambulatory heart failure patient. These waveforms provide significant insights into patient volume and clinical management. We aim to provide a foundation for understanding the determinants of waveform characteristics and provide practical examples illustrating how to interpret and integrate common scenario waveforms into clinical decision-making. A total of three groups of relevant scenarios were included namely (a) location and activity at time of waveform transmission, (b) impact of contemporary interventions, and (c) arrhythmias. We illustrate that waveform analysis can be individualized to each patient's care strategy in the appropriate clinical context to help guide clinical decision-making.
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