Rachel Klemovitch, Assistant Editor03.08.24
Bioport virtual care company presented data on its non-invasive, FDA-cleared, biomarker-based technology for remote heart failure monitoring. It detected twice as many heart failure events compared to the weight-based standard of care.
Research from a preliminary analysis of Bodyport’s SCALE-HF 1 study was presented at the Cardiovascular Research Foundation’s third annual Technology and Heart Failure Therapeutics (THT) conference on March 4-6.
“These findings represent a notable improvement of the standard of care, which has patients stepping on a weight scale each day to detect worsening heart failure. This biomarker-based technology also utilizes the familiar patient routine of stepping onto a scale, but the scale’s sensors and algorithms have doubled the number of predicted heart failure events, significantly boosting the utility of remote monitoring to head off the kinds of serious complications that can lead to hospitalization,” said Marat Fudim, MD, MHS, who presented the data and is an advanced heart failure specialist and cardiologist with Duke University Medical Center.
329 people across 8 sites participated in the SCALE-HF 1 prospective observational study with 238 patient-years of follow-up. Participants took measurements at home using the Bodyport Cardiac Scale, a non-invasive device with the familiar form factor of a weight scale.
The gathered data included congestion-related biomarkers from the device that were used as inputs in Bodyport’s Congestion Index algorithm. In the SCALE-HF 1 study, the Congestion Index was able to accurately predict heart failure events (HFEs). The study defined these events as unplanned administration of IV diuretics or hospital admissions with heart failure as the primary diagnosis.
The Congestion Index correctly predicted 48 of 69 HFEs throughout the study, demonstrating a significantly higher sensitivity (p<0.01) than the weight-scale standard of care. The standard weight rule detected 24 of 69 HFEs.
The Congestion Index also detected a lower alert rate, generating 2.58 alerts per patient-year compared to 4.18 by the standard of care.
The mean age of participants was 64, 43% were women, and 32% were black; 56% of patients had a ventricular ejection fraction of /=50%.
“This should be welcome news for patient care teams because a greater prediction rate with fewer false alerts translates into more effective and efficient care,” said Bodyport founder, president, and CEO at Corey Centen. “What’s more, use of the Cardiac Scale and the Congestion Index is a seamless transition for clinicians and patients because it enhances, rather than replaces, the existing pathways built around weight monitoring. 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.”
Research from a preliminary analysis of Bodyport’s SCALE-HF 1 study was presented at the Cardiovascular Research Foundation’s third annual Technology and Heart Failure Therapeutics (THT) conference on March 4-6.
“These findings represent a notable improvement of the standard of care, which has patients stepping on a weight scale each day to detect worsening heart failure. This biomarker-based technology also utilizes the familiar patient routine of stepping onto a scale, but the scale’s sensors and algorithms have doubled the number of predicted heart failure events, significantly boosting the utility of remote monitoring to head off the kinds of serious complications that can lead to hospitalization,” said Marat Fudim, MD, MHS, who presented the data and is an advanced heart failure specialist and cardiologist with Duke University Medical Center.
329 people across 8 sites participated in the SCALE-HF 1 prospective observational study with 238 patient-years of follow-up. Participants took measurements at home using the Bodyport Cardiac Scale, a non-invasive device with the familiar form factor of a weight scale.
The gathered data included congestion-related biomarkers from the device that were used as inputs in Bodyport’s Congestion Index algorithm. In the SCALE-HF 1 study, the Congestion Index was able to accurately predict heart failure events (HFEs). The study defined these events as unplanned administration of IV diuretics or hospital admissions with heart failure as the primary diagnosis.
The Congestion Index correctly predicted 48 of 69 HFEs throughout the study, demonstrating a significantly higher sensitivity (p<0.01) than the weight-scale standard of care. The standard weight rule detected 24 of 69 HFEs.
The Congestion Index also detected a lower alert rate, generating 2.58 alerts per patient-year compared to 4.18 by the standard of care.
The mean age of participants was 64, 43% were women, and 32% were black; 56% of patients had a ventricular ejection fraction of /=50%.
“This should be welcome news for patient care teams because a greater prediction rate with fewer false alerts translates into more effective and efficient care,” said Bodyport founder, president, and CEO at Corey Centen. “What’s more, use of the Cardiac Scale and the Congestion Index is a seamless transition for clinicians and patients because it enhances, rather than replaces, the existing pathways built around weight monitoring. 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.”