4.7 Article

Association between Remote Dielectric Sensing and Estimated Plasma Volume to Assess Body Fluid Distribution

Journal

JOURNAL OF CLINICAL MEDICINE
Volume 12, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/jcm12020463

Keywords

congestion; heart failure; hemodynamics

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Pulmonary congestion is measured by the ReDS system, while systemic congestion is estimated by calculated plasma volume. The association between these two parameters and the type of patient profile remains uncertain. This study aims to assess the relationship between ReDS values and plasma volume status.
Background: Pulmonary congestion is quantified by a remote dielectric sensing (ReDS (TM)) system, while systemic congestion is estimated by calculated plasma volume. The type of clinical patient profile as defined by the ReDS system and calculated plasma volume remains uncertain. Methods: Hospitalized patients with or without heart failure were included in this prospective study. On admission, ReDS values were measured and plasma volume status (PVS) was estimated using their body weight at the same time. Cutoffs of ReDS value and PVS were defined at 34% and -2.7%, respectively. The association between the two parameters was assessed. Results: A total of 482 patients (median 76 years, 288 men) were included. The median ReDS value was 28% (25%, 32%) and median PVS was -16.4% (-26.3%, -5.9%). Of the patients, 64 had high ReDS value (and low PVS) and 80 had high PVS (and low ReDS value). The high ReDS group had a higher prevalence of clinical heart failure with a more elevated echocardiographic E/e' ratio, whereas the high PVS group had a higher prevalence of chronic kidney disease (p < 0.05 for all). Four out of a total of six patients with high ReDS value and high PVS had both heart failure and chronic kidney disease profiles. Conclusion: The combination of ReDS value and PVS was able to clinically stratify the types of body fluid distribution and patient profiles. Utilizing these tools may assist the clinician in constructing a therapeutic strategy for the at-risk hospitalized patient.

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