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This is a pilot/feasibility study on the accuracy of HRV as measured by the Apple Watch on heart failure patients who are admitted to the hospital with heart failure exacerbation. The primary aim is to observe a statistically significant improvement in the HRV of acutely decompensated heart failure patients upon discharge when compared to admission, implying the utility of HRV measured by Apple Watch as a monitor for cardiovascular health.
Heart failure (HF) is a complex clinical syndrome. It is caused by structural or functional impairments, which interfere with the ability of heart muscles to fill or eject blood. The prevalence of HF exceeds 7 million in the United States alone.(1) Despite improving survival, HF hospitalization rates has remained stable, which reflects persisting difficulties in managing existing disease. (2) Specifically, readmission rates may be as high as 50% by 6 months after an admission for HF management. (2) Caring for HF patients exceeds 30 billion annually and is largely driven by hospitalizations.2 Innovative, at-home surveillance tools are needed to reduce hospital admissions and to drive down the overall societal burden of this disease. (3)
HF is characterized by periodic exacerbations due to volume overload and fluid congestion that impairs perfusion to the organs.(2) Accurate assessment of volume status is, therefore, key for early detection of impending exacerbation. Currently, there is no single, objective method of assessment, relying on a combination of tools including physical examination, weight, pulmonary artery catheter or echocardiography.(4) However, these measures are subjective, invasive, or impractical for monitoring patients at home. Unique body habitus and comorbidities of individual patient further complicates assessment of volume status.(4) The future of heart failure management, therefore, lies in the development of a telemonitoring system that is convenient to use and accessible for patients at home, while quantitatively understanding individual characteristics.(4)
Cardiovascular health is closely related to the imbalances of the autonomic nervous system.(5) Heart rate variability (HRV), the degree of fluctuation in the interval between consecutive heartbeats, has been recognized as a reliable marker of autonomic activity.(5) HRV has been shown to be depressed in patients with congestive heart failure (CHF) and to correlate with disease severity. (6) Furthermore, abnormal HRV parameters are independently associated with incident CHF in asymptomatic, older adults. (7)
HRV is conventionally measured using a 24-hour Holter monitor, which is sensitive, but inconvenient and impractical for home monitoring.(5) Newer studies have shown not only the reliability of short term (5-minute) or ultra-short term (<5 minute) analysis of electrocardiographic recordings, but also that of wearable monitors amenable for use at home.(9-11) In particular, HRV parameters measured by Apple Watch (Cupertino, California) were shown to agree with those measured by a validated chest best heart rate monitor.(12)
The usefulness of the study is to validate the utility of wearable heart monitors such as the Apple Watch in accurately measuring heart rate variability, a dynamic marker of cardiovascular health, and correlating it with the health status specifically of heart failure patients. Validating this will allow wearable monitors to record HRV remotely from home, facilitating telemonitoring and preventing hospitalizations.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Heart Failure Patients | Experimental | This will be a single arm study of heart failure patients with acute decompensation |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Apple Watch | Device | Apple Watch is a smartwatch developed by Apple Inc. The heart rate variability function will be used. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Difference of Standard Deviation of NN Intervals upon Discharge Compared to Admission | Standard Deviation of NN Intervals is a time domain heart rate variability parameter. The value upon discharge after medical management should be statistically greater compared to admission value. | 1-2 Weeks |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Tufts Medical Center | Boston | Massachusetts | 02111 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23989710 | Background | Roger VL. Epidemiology of heart failure. Circ Res. 2013 Aug 30;113(6):646-59. doi: 10.1161/CIRCRESAHA.113.300268. | |
| 22331920 | Background | Desai AS. Home monitoring heart failure care does not improve patient outcomes: looking beyond telephone-based disease management. Circulation. 2012 Feb 14;125(6):828-36. doi: 10.1161/CIRCULATIONAHA.111.031179. No abstract available. |
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| ID | Term |
|---|---|
| D006333 | Heart Failure |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| 18550924 | Background | Murray CM, Agha SA, Rathi S, Germany RE. The evaluation and monitoring of volume status in congestive heart failure. Congest Heart Fail. 2008 May-Jun;14(3):135-40. doi: 10.1111/j.1751-7133.2008.05640.x. |
| 8737210 | Background | Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Eur Heart J. 1996 Mar;17(3):354-81. No abstract available. |
| 14502297 | Background | Musialik-Lydka A, Sredniawa B, Pasyk S. Heart rate variability in heart failure. Kardiol Pol. 2003 Jan;58(1):10-6. |
| 28396041 | Background | Patel VN, Pierce BR, Bodapati RK, Brown DL, Ives DG, Stein PK. Association of Holter-Derived Heart Rate Variability Parameters With the Development of Congestive Heart Failure in the Cardiovascular Health Study. JACC Heart Fail. 2017 Jun;5(6):423-431. doi: 10.1016/j.jchf.2016.12.015. Epub 2017 Apr 5. |
| 24490775 | Background | Ferrario M, Moissl U, Garzotto F, Cruz DN, Clementi A, Brendolan A, Tetta C, Gatti E, Signorini MG, Cerutti S, Ronco C. Effects of fluid overload on heart rate variability in chronic kidney disease patients on hemodialysis. BMC Nephrol. 2014 Feb 4;15:26. doi: 10.1186/1471-2369-15-26. |
| 21496161 | Background | Nussinovitch U, Elishkevitz KP, Katz K, Nussinovitch M, Segev S, Volovitz B, Nussinovitch N. Reliability of Ultra-Short ECG Indices for Heart Rate Variability. Ann Noninvasive Electrocardiol. 2011 Apr;16(2):117-22. doi: 10.1111/j.1542-474X.2011.00417.x. |
| 19690410 | Background | Karp E, Shiyovich A, Zahger D, Gilutz H, Grosbard A, Katz A. Ultra-short-term heart rate variability for early risk stratification following acute ST-elevation myocardial infarction. Cardiology. 2009;114(4):275-83. doi: 10.1159/000235568. Epub 2009 Aug 18. |
| 30103376 | Background | Hernando D, Roca S, Sancho J, Alesanco A, Bailon R. Validation of the Apple Watch for Heart Rate Variability Measurements during Relax and Mental Stress in Healthy Subjects. Sensors (Basel). 2018 Aug 10;18(8):2619. doi: 10.3390/s18082619. |
| 22642636 | Background | Tanindi A, Olgun H, Celik B, Boyaci B. Heart rate variability in patients hospitalized for decompensated diastolic heart failure at admission and after clinical stabilization. Future Cardiol. 2012 May;8(3):473-82. doi: 10.2217/fca.12.24. |