Wearable Remote Monitoring of Heart Rate and Respiratory Rate for Heart Failure
Wearable Remote Monitoring of Heart Rate and Respiratory Rate for Heart Failure
The primary objective of this study is to study in heart failure (HF) patients to better
 assess HF disease state, which can aid in management and improve outcomes. Primary aims of
 the study include: (1) Measure HR and RR at rest and during daily activity using the WHOOP
 device. (2) Correlate HR and RR response to activity to New York Heart Association (NYHA)
 class and 90-day HF hospitalization rate. (3) Identify additional predictors of NYHA class
 and HF hospitalization rate for algorithm development to use the WHOOP device as a clinical
 tool for HF management.
Heart Failure (HF) is a challenging condition to manage, with hospital readmission for HF
 exacerbation having negative impacts on patient outcomes and financial burden to both patient
 and health system [Lloyd-Jones, 2010; Yancy, 2017; Ross, 2009; Chaudhry, 2007]. An intuitive
 need for more sensitive predictors of HF exacerbations has led researchers to explore remote
 monitoring as a possible answer. Consumer-owned sensors have become more accurate in their
 recording of vital signs, and thus could hold potential for remote monitoring [Dickinson,
 2018]. The combined measure of heart rate (HR) and respiratory rate (RR) has been shown to
 predict New York Heart Association (NYHA) HF class, an indicator of severity of heart
 disease, in implantable cardiac devices with multi-sensor monitoring capabilities [Auricchio,
 2014; Prasun, 2019; Boehmer, 2015; Boehmer, 2017]. Heart rate variability (HRV), a measure of
 sympathetic autonomic function, has also shown potential in prediction of adverse cardiac
 events [Al-Zaiti, 2019; Shaffer, 2017; Bullinga, 2005; Tsuji, 1996].

 The WHOOP device, a wearable strap similar to a Fitbit, allows for real-time HR monitoring
 and can determine RR using respiratory sinus arrhythmia [www.whoop.com/experience; Berryhill,
 2020]. It is one of the few devices on the market that can accurately track heart rate as
 well as respiratory rate in real-time (during activity) and is equipped with a
 multidirectional accelerometer for activity tracking. The WHOOP device was recently
 externally validated against polysomnography and continuous electroencephalogram (EEG) for
 sleep tracking, and continuous electrocardiogram (ECG) for HR and HRV (with less than 5%
 error) [Berryhill, 2020]. HRV, which represents the balance of the sympathetic and
 parasympathetic nervous systems, is a known predictor of cardiac events. It is especially
 useful in HF, which is a chronically elevated catecholamine state leading to depressed HRV
 and is tied to NYHA HF class, an indicator of severity of disease [Bullinga, 2005; Tsuji,
 1996].

 Data so far regarding the efficacy of remote physiologic monitoring using cardiac implantable
 electronic devices (CIEDs), although promising in theory, has not yet proved sensitive in the
 detection of HF exacerbation. The aim of the CLEPSYDRA study was to use data extracted from
 implanted cardiac resynchronization therapy with defibrillation (CRT-D) devices in HF
 patients to predict heart failure events; although the main variables used in the novel
 algorithm, minute ventilation and patient activity, would intuitively seem to be predictors
 of poor outcome/HF exacerbation, the sensitivity of the algorithm to predict an event was
 only 34% [6]. It would appear that this combination of variables is not sufficient to predict
 adverse HF events. However, the HOME-CARE (HOME Monitoring in CArdiac REsynchronization
 Therapy) study showed more promising results, as their enhanced predictor, utilizing seven
 diagnostic variables from implanted CRT-Ds, boasted a sensitivity of 65.4% [Sack, 2011].
 While the data from these studies is helpful, no study has been able to adequately identify
 and assess accurate predictors of HF class.

 Current efficacious management strategies are limited to hemodynamic or multisensor
 monitoring systems. However, these are only available in implanted cardioverter-defibrillator
 (ICD) or cardiac resynchronization therapy-defibrillator (CRT-D) devices. These are not
 implanted in every HF patient [Al-Zaiti, 2019]. Non-invasive monitoring that provides similar
 data, such as wearable device monitoring, would expand the cohort of patients that would
 benefit from remote monitoring and would avoid the risks of having implanted hardware.
 Furthermore, better prediction of HF severity could help guide follow-up care and predict HF
 events [Boehmer, 2015; Boehmer 2017]. This would lead to more efficient management, less
 hospital readmission, and improve outcomes for HF patients overall [Dickinson, 2018].

 The investigators propose a feasibility study in HF patients to better assess HF disease
 state, which can aid in management and improve outcomes. Subjects will wear the WHOOP device,
 which measures both activity and HR parameters and can derive RR using respiratory sinus
 arrhythmia, for 90 days. During this period, their HR and RR will be recorded at rest, during
 activity and post-activity recovery phases. This combined measure of HR/RR has been shown to
 predict NYHA HF class, an indicator of severity of disease, in implantable devices with
 multi-sensor monitoring capabilities; thus, it represents a useful management strategy in HF
 patients [Bullinga, 2005; Tsuji, 1996]. A continuous external monitoring device worn on the
 wrist, such as the WHOOP device, would provide valuable physiologic data for a cohort of HF
 patients who were previously unable to be monitored in this fashion. Secondary analysis of
 this study will investigate the use of intra- and post-activity HR and RR as predictors of
 hospitalization rates, a common problem in HF patients that correlate with worse mortality
 outcomes.
Inclusion Criteria:

 1. Subject has provided informed consent

 2. Male or female over the age of 18 years

 3. The patient is either hospitalized with a primary diagnosis of acute heart failure or
 was discharged with a primary diagnosis of acute heart failure within 2 weeks prior to
 enrollment; or carries a diagnosis of heart failure and is seen as an outpatient at
 Hershey Medical Center.

 4. NYHA functional class II-IV at time of enrollment

 5. Subject willing to wear the WHOOP for the 90-day study period.

 6. Subject owns a phone for pairing with the WHOOP device (required for data storage and
 transfer)

 Exclusion Criteria:

 1. Subjects who are limited by angina.

 2. Subjects with severe aortic stenosis.

 3. Subjects who are hemodynamically unstable requiring support with intravenous
 vasoactive medications or mechanical circulatory support

 4. Subjects with symptomatic ventricular arrhythmias within the past 6 months.