Use of ReDS Technology in Patients With Acute Heart Failure (NCT04305717)

🩺 Plain-English Summary (8th-Grade Level)

Background: Fluid overload, especially pulmonary congestion, is one of the main contributors into heart failure (HF) readmission risk and it is a clinical challenge for clinicians. The Remote dielectric sensing (ReDS) system is a novel electromagnetic energy-based technology that can accurately quantify changes in lung fluid concentration noninvasively. Previous non-randomized studies suggest that ReDS-guided management has the potential to reduce readmissions in HF patients recently discharged from the hospital. Aims: To test whether a ReDS-guided strategy during HF admission is superior to the standard of care during a 1-month follow up. Methods: The ReDS-SAFE HF trial is an investigator-initiated, single center, single blind, 2-arm randomized clinical trial, in which \~240 inpatients with acutely decompensated HF at Mount Sinai Hospital will be randomized to a) standard of care strategy, with a discharge scheme based on current clinical practice, or b) ReDS-guided strategy, with a discharge scheme based on specific target value given by the device on top of the current clinical practice. ReDS tests will be performed for all study patients, but results will be blinded for treating physicians in the "standard of care" arm. The primary outcome will be a composite of unplanned visit for HF that lead to the use of intravenous diuretics, hospitalization for worsening HF, or death from any cause at 30 days after discharge. Secondary outcomes including the components of the primary outcome alone, length of stay, quality of life, time-averaged proportional change in the natriuretic peptides plasma levels, and safety events as symptomatic hypotension, diselectrolytemias or worsening of renal function. Conclusions: The ReDS-SAFE HF trial will help to clarify the efficacy of a ReDS-guided strategy during HF-admission to improve the short-term prognosis of patients after a HF admission.

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Location: Mount Sinai Hospital — New York, New York

Age range: 18 Years