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Collected enough data to support the Endpoints
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| Name | Class |
|---|---|
| Food and Drug Administration (FDA) | FED |
| Mayo Clinic | OTHER |
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Heart Failure (HF) is a highly prevalent disease that also carries high morbidity and mortality. The Food and Drug Administration (FDA) recognizes the importance of developing patient-centric endpoints that are relevant to patients beyond mortality and hospitalizations.
Although functional status can be objectively measured by peak exercise oxygen consumption, it is difficult and impractical to implement in large clinical studies, especially in an ambulatory real-world setting. Recently, new mobile health technologies have emerged as clinical tools and offer an opportunity to overcome these challenges in measuring functional capacity and recording symptoms.
The goal of this observational study is to evaluate the feasibility of monitoring functional capacity among patients with heart failure (HF) using mobile health monitoring platforms.
Everion® and Apple Watch Series 4 and above will be used for this study. The BiovitalsHF® mobile app can capture patients' key cardiopulmonary physiological parameters, functional capacity (using activity patterns, including guided mobile-based 6MWT, audio recording) and assessment of QoL through validated PROs.
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| Measure | Description | Time Frame |
|---|---|---|
| Feasibility of monitoring functional capacity among patients using mobile health monitoring platform | Measurement of correlation between physiology and accelerometer (activity) data/derivatives with:
| 8 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Compliance rate | Compliance rate to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform | 8 weeks |
| Drop-out rate | Drop-out rate to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform |
| Measure | Description | Time Frame |
|---|---|---|
| Percentage of patients on HF GDMT | Percentage of patients on beta blocker, ACE/ARN/ or ARNI and MRA | 8 weeks |
| Percentage of patients on target dose of HF GDMT | Target dose of HF GDMT is according to 2021 Update to the 2017 ACC Expert Consensus Decision Pathway for Optimization of Heart Failure Treatment |
Inclusion Criteria:
Subjects are eligible to be included in the study only if all the following criteria apply:
Subjects has provided informed consent prior to initiation of any study specific activities/procedures.
Exclusion Criteria
Subjects are excluded from the study if any of the following criteria apply:
Disease Related
Other Medical Conditions
Prior/Concomitant Medication
1. Currently receiving treatment or procedure in another investigational device or drug study.
Other Exclusions
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Approximately 150 eligible subjects will be enrolled into the study. Eligible subjects will include adults with a diagnosis of heart failure (NYHA class I to class III), and screened within 30 days after Clinic Visit or hospitalization for heart failure - either as a primary or secondary diagnosis.
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| Name | Affiliation | Role |
|---|---|---|
| Maulik Majmudar, M.D. | Biofourmis Inc. | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Mayo Clinic | Jacksonville | Florida | 32224 | United States | ||
| National University Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23141494 | Background | Campbell RT, Jhund PS, Castagno D, Hawkins NM, Petrie MC, McMurray JJ. What have we learned about patients with heart failure and preserved ejection fraction from DIG-PEF, CHARM-preserved, and I-PRESERVE? J Am Coll Cardiol. 2012 Dec 11;60(23):2349-56. doi: 10.1016/j.jacc.2012.04.064. Epub 2012 Nov 7. | |
| 27756791 | Background |
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| ID | Term |
|---|---|
| D006333 | Heart Failure |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| 8 weeks |
| Mean time worn/day | Mean time worn/day to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform | 8 weeks |
| Proportion of time worn that device produces reliable data | Proportion of time worn that device produces reliable data to measure the feasibility of collecting continuous, biometrics data and ePROs using mobile-health monitoring platform | 8 weeks |
| 8 weeks |
| Unplanned hospital visits of patients on HF GDMT and target dose of GDMT | 30-days hospitalization, Clinic visits and ED visits, and its correlation to patients on HF GDMT and target dose of GDMT | 8 weeks |
| Questionnaire for patient experience | Questionnaire to evaluate the subjects' experience with the mobile device(s) and mobile health monitoring platform | 8 weeks |
| Association of ECG/Vitals/voice-related biomarker to progression of HF disease | Ability to detect changes in ECG/Vitals/voice biomarker, and correlate with functional status and clinical outcomes | 8 weeks |
| Singapore |
| 119074 |
| Singapore |
| National Heart Centre Singapore | Singapore | 169609 | Singapore |
| Tan Tock Seng Hospital | Singapore | 308433 | Singapore |
| Changi General Hospital | Singapore | 529889 | Singapore |
| Khoo Teck Puat Hospital | Singapore | 768828 | Singapore |
| Butler J, Hamo CE, Udelson JE, Pitt B, Yancy C, Shah SJ, Desvigne-Nickens P, Bernstein HS, Clark RL, Depre C, Dinh W, Hamer A, Kay-Mugford P, Kramer F, Lefkowitz M, Lewis K, Maya J, Maybaum S, Patel MJ, Pollack PS, Roessig L, Rotman S, Salsali A, Sims JJ, Senni M, Rosano G, Dunnmon P, Stockbridge N, Anker SD, Zile MR, Gheorghiade M. Exploring New Endpoints for Patients With Heart Failure With Preserved Ejection Fraction. Circ Heart Fail. 2016 Nov;9(11):e003358. doi: 10.1161/CIRCHEARTFAILURE.116.003358. |
| 25488549 | Background | Palau P, Nunez E, Dominguez E, Sanchis J, Nunez J. Physical therapy in heart failure with preserved ejection fraction: A systematic review. Eur J Prev Cardiol. 2016 Jan;23(1):4-13. doi: 10.1177/2047487314562740. Epub 2014 Dec 8. |
| 9699234 | Background | Hsieh FY, Bloch DA, Larsen MD. A simple method of sample size calculation for linear and logistic regression. Stat Med. 1998 Jul 30;17(14):1623-34. doi: 10.1002/(sici)1097-0258(19980730)17:143.0.co;2-s. |