Surveillance and Alert-based Multiparameter Monitoring to Reduce Worsening Heart Failure Events: Results From SCALE-HF 1.

BACKGROUND: There is a need for better noninvasive remote monitoring solutions that prevent hospitalizations through the early prediction and management of heart failure (HF). SurveillanCe and Alert-Based Multiparameter Monitoring to ReducE Worsening Heart Failure Events (SCALE-HF 1) evaluated the performance of a novel congestion index that alerts to fluid accumulation preceding HF events. METHODS AND RESULTS: SCALE-HF 1 was a multicenter, prospective, observational study investigating HF event prediction using data from the cardiac scale. Participants with HF took measurements at home by standing barefoot on the scale for approximately 20 seconds each day. The congestion index was applied retrospectively, and an alert was generated when the index exceeded a fixed threshold established in prior studies. HF events were defined as unplanned administration of IV diuretics or admissions with a primary diagnosis of HF. Sensitivity was defined as the ratio of correctly identified HF events to the total number of HF events. We enrolled 329 participants (mean age 64 ± 14 years; 43% women; 32% Black; 56% with reduced ejection fraction) across 8 sites with 238 participant-years of follow-up and 69 usable HF events. The congestion index predicted 48 of the 69 HF events (70%) at 2.58 alerts per participant-year. In contrast, the standard weight rule (weight gain of >3 lb in 1 day or >5 lb in 7 days) predicted only 24 of the 69 HF events (35%) at 4.18 alerts per participant-year. The congestion index alerts had a significantly higher sensitivity (P < .01) at a lower alert rate than the standard weight rule. CONCLUSIONS: The congestion index alerts demonstrated sensitive prediction of HF events at a low alert rate, significantly exceeding the performance of weight-based monitoring. GOV IDENTIFIER: NCT04882449.

Use of a Cardiac Scale to Predict Heart Failure Events: Design of SCALE-HF 1.

BACKGROUND: There is a need for simple, noninvasive solutions to remotely monitor and predict worsening heart failure (HF) events. SCALE-HF 1 (Surveillance and Alert-Based Multiparameter Monitoring to Reduce Worsening Heart Failure Events) is a prospective, multicenter study that will develop and assess the accuracy of the heart function index-a composite algorithm of noninvasive hemodynamic biomarkers from a cardiac scale-in predicting worsening HF events. METHODS: Approximately 300 patients with chronic HF and recent decompensation will be enrolled in this observational study for model development. Patients will be encouraged to take daily cardiac scale measurements. RESULTS: Approximately 50 HF events, defined as an urgent, unscheduled clinic, emergency department, or hospitalization for worsening HF will be used for model development. The composite index will be developed from hemodynamic biomarkers derived from ECG, ballistocardiogram, and impedance plethysmogram signals measured from the cardiac scale. Biomarkers of interest include weight, peripheral impedance, pulse rate and variability, and estimates of stroke volume, cardiac output, and blood pressure captured through the cardiac scale. The sensitivity, unexplained alert rate, and alerting time of the index in predicting worsening HF events will be evaluated and compared with the performance of simple weight-based rule-of-thumb algorithms (eg, weight increase of 3 lbs in 1 day or 5 lbs in 7 days) that are often used in practice. CONCLUSIONS: SCALE-HF 1 is the first study to develop and evaluate the performance of a composite index derived from noninvasive hemodynamic biomarkers measured from a cardiac scale in predicting worsening HF events. Subsequent studies will validate the heart function index and assess its ability to improve patient outcomes. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT04882449.

Noninvasive Scale Measurement of Stroke Volume and Cardiac Output Compared With the Direct Fick Method: A Feasibility Study.

Background Objective markers of cardiac function are limited in the outpatient setting and may be beneficial for monitoring patients with chronic cardiac conditions. We assess the accuracy of a scale, with the ability to capture ballistocardiography, electrocardiography, and impedance plethysmography signals from a patient's feet while standing on the scale, in measuring stroke volume and cardiac output compared with the gold-standard direct Fick method. Methods and Results Thirty-two patients with unexplained dyspnea undergoing level 3 invasive cardiopulmonary exercise test at a tertiary medical center were included in the final analysis. We obtained scale and direct Fick measurements of stroke volume and cardiac output before and immediately after invasive cardiopulmonary exercise test. Stroke volume and cardiac output from a cardiac scale and the direct Fick method correlated with r=0.81 and r=0.85, respectively (P<0.001 each). The mean absolute error of the scale estimated stroke volume was -1.58 mL, with a 95% limits of agreement of -21.97 to 18.81 mL. The mean error for the scale estimated cardiac output was -0.31 L/min, with a 95% limits of agreement of -2.62 to 2.00 L/min. The changes in stroke volume and cardiac output before and after exercise were 78.9% and 96.7% concordant, respectively, between the 2 measuring methods. Conclusions In a proof-of-concept study, this novel scale with cardiac monitoring abilities may allow for noninvasive, longitudinal measures of cardiac function. Using the widely accepted form factor of a bathroom scale, this method of monitoring can be easily integrated into a patient's lifestyle.