Scale using biosensor technology detects HF events more often than standard of care
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Key takeaways:
- A congestion index derived from a scale using biosensor technology predicted heart failure events better than weight alone.
- The congestion index had a lower alert rate than standard weight-based monitoring.
A congestion index derived from a scale using biosensor technology better predicted heart failure events compared with standard weight-based monitoring, researchers reported at the Technology and Heart Failure Therapeutics annual meeting.
For the SCALE-HF 1 study, the researchers enrolled 329 patients with HF with reduced, preserved or midrange ejection fraction (mean age, 64 years; 43% women; 32% Black) who stood on the cardiac scale (Bodyport) for approximately 20 seconds per day to measure their weight and peripheral impedance, from which a congestion index was derived. The ability of the congestion index to predict HF events was compared with the ability of standard weight-based monitoring, in which an alert is sent if weight gain exceeds 3 lb in 1 day or 5 lb in 7 days.
“Biosensors built into the scale surface measure several FDA-cleared biomarkers of heart function and fluid status, which accurately reflect worsening heart failure,” Marat Fudim, MD, MHS, cardiologist and advanced heart failure specialist at Duke University Medical Center, who presented the data at THT, told Healio. “The data captured by the scale is then transmitted via cellular technology to a clinical dashboard, a patient app and a monitoring team. The Bodyport cardiac scale has been FDA-cleared for monitoring patients with fluid management conditions and all biomarkers have been validated and peer-reviewed against the gold standards. The Bodyport platform is noninvasive, the workflow is familiar to patients, and measurements take just 20 seconds or less.”
During 238 patient-years of follow-up, there were 69 HF events that could be used for the analysis.
The congestion index had a higher rate of sensitivity than standard weight-based monitoring (70% vs. 35%; P < .01), with a lower alert rate (2.58 per patient-year vs. 4.18 per patient-year), according to the researchers.
“Doubling the number of predicted heart failure events is key, as it fuels earlier intervention and thus a reduction in the serious complications that can ultimately lead to hospitalization,” Fudim told Healio. “The lower alert rate should lead to workflow efficiencies because care teams — who are often feeling overly burdened by the large number of notifications and data flowing in — will spend less time responding to false alerts. There was a broad range of patients enrolled in this study, meaning the congestion index is applicable across the broad range of heart failure patients.
“Bodyport is still studying prospective use of the Bodyport cardiac scale and congestion index, but the hope is that it reduces heart failure admissions, empowers patients with data that can help them manage their condition and improves quality of life for patients with HF,” Fudim told Healio.
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Fudim M, et al. Featured late-breaking clinical science abstracts III. Presented at: Technology and Heart Failure Therapeutics (THT); March 4-6, 2024; Boston.
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