Wearable Devices in Cardiovascular Risk Assessment, Cardiovascular Disease Prevention, Diagnosis, and Management
Wearables in Atrial Fibrillation Risk Assessment and Management
The role of physical activity as a modifiable risk factor for the development of AF was studied recently in a well-organized prospective study, which included 93 669 participants from the UK Biobank prospective cohort, without a prevalent history of AF, who wore a wrist-based triaxial accelerometer for 1 week. The sensor captured acceleration at 100 Hz with a dynamic range of ±8 g. The primary outcome of the study was incident AF.
According to the findings of the study, greater accelerometer-derived physical activity is associated with a lower risk of incident AF and stroke, after adjustment for clinical risk factors (Figure 2). Wearable sensors may enable both objective assessment of physical activity and modification of AF risk through targeted feedback. The authors consider that future preventive efforts to reduce AF risk may be most effective if they target adherence to objective activity thresholds.
Cumulative risks of atrial fibrillation (upper panel) and stroke (lower panel) stratified by adherence to physical activity recommendations, as validated by accelerometer-derived physical activity. Reproduced by permission from Khurshid et al.55
Another study that aimed to investigate the association between changes in physical activity and the onset of AF reported similar findings. A total of 1410 participants from the general population were studied (46.2% women, mean age 74.7 ± 4.1 years), with risk factors but with no prior AF diagnosis, who underwent continuous monitoring for AF episodes along with daily accelerometric assessment of physical activity, using an implantable loop recorder, over an average period of 3.5 years.
According to the findings of the study, intra-individual changes in physical activity were associated with the onset of AF episodes, as detected by continuous monitoring, in a high-risk population. For each person, a 1 h decrease in daily physical activity during the previous week increased the odds of AF onset the next day by ~25%, while the strongest association was seen in the group with the lowest activity overall.
Apart from these two recent and revealing studies of the relationship between a person's physical activity and the occurrence of AF, a significant number of ongoing or recently published studies have evaluated the capabilities of wearables, focusing on the relationship between the individual clinical outcome and the burden of recorded episodes of clinical or subclinical AF.
Wearables in Heart Failure Assessment and Management
Heart failure (HF), a fast-growing disease internationally, also has a long-standing affinity with wearable technology, since the pathophysiology of the disease and its clinical consequences require close and continuous long-term monitoring. Indeed, wearables offer a unique opportunity to assess patients' status and a number of indicators closely, outside the classical settings. In patients with HF, data from consumer wearables, such as physical activity step count or heart rate, but also more intense monitoring of such factors as pulmonary artery pressure or fluid retention, have long been the target of these evolving devices.
When we look at the findings and messages of the most recent relevant studies, those of the LINK-HF multicentre study by Stehlik et al., which evaluated the accuracy of non-invasive remote monitoring in predicting rehospitalization for HF, were quite revealing. This was a study of 100 patients with HF, aged 68.4 ± 10.2 years (only 2% female). The investigators showed that multivariate physiological telemetry from a wearable sensor, in combination with machine learning analytics, can accomplish accurate early detection of impending rehospitalization with a predictive accuracy comparable to that of implantable devices. The authors emphasize, however, that the clinical efficacy and generalizability of this low-cost non-invasive approach to rehospitalization mitigation still needs further testing.
Looking at the issues more broadly, apart from the use of modern electronic technology for continuous haemodynamic monitoring in HF patients, it has become clear that such technology can and should be used for education and support in these patients' therapeutic management.
The EPIC-HF study (Electronically Delivered Patient-Activation Tool for Intensification of Medications for Chronic Heart Failure with Reduced Ejection Fraction) evaluated patients from a diverse health system who had HF and reduced ejection fraction, randomizing them to usual care vs. patient activation tools. The tools—a 3 min video and a one-page checklist—encouraged patients to work collaboratively with their clinicians to 'make one positive change' in their HF medication.
The findings were clear. A patient activation tool delivered electronically before the cardiology clinic visit enhanced clinicians' intensification of guideline-directed medical therapies.
ST-segment Elevation Myocardial Infarction
The vast majority of wearable devices currently offer single-lead ECG recording, which allows the detection of AF and, more rarely, other arrhythmias to a satisfactory extent. However, such ECG recordings cannot reliably detect ST/T changes due to regional myocardial ischaemia. Nevertheless, a good many expectations have been invested in this possibility, as ECG recording by wearables, backed by telemonitoring to detect the early signs of myocardial ischaemia, could limit its often destructive effects.
Muhlestein et al., in their relatively recent publication, reviewed the feasibility of combining serial smartphone single-lead recordings to create a virtual 12-lead ECG capable of reliably diagnosing ST-elevation myocardial infarction. The study included 200 subjects (mean age 60 years, 43% female).
For all interpretable pairs of smartphone ECGs, compared with standard 12-lead ECGs (n = 190), the sensitivity, specificity, and positive and negative predictive values for ST-segment elevation myocardial infarction (STEMI) or STEMI equivalent (left bundle branch block) achieved by the smartphone were 0.89, 0.84, 0.70, and 0.95, respectively. The authors concluded that a 12-lead equivalent ECG constructed from multiple serial single-lead recordings from a smartphone can identify STEMI with a good correlation to a standard 12-lead ECG.
Similar to the previous study, a prospective study also investigated the feasibility and accuracy of a smartwatch in recording multiple electrocardiographic leads and detecting ST-segment changes associated with ACS, compared with a standard 12-lead ECG. A commercially available smartwatch was used in 100 participants. The watch was placed in different body positions to obtain nine bipolar ECG tracings (corresponding to Einthoven leads, II and III, and precordial leads, V1–V6), which were compared with a simultaneous standard 12-lead ECG.
To a significant extent, there was an agreement between the findings of the smartwatch tracings and the standard ECGs for the identification of a normal ECG, ST-segment changes, and no ST-segment elevation.
The findings of the two previous studies give cause for optimism that, in the near future, the technical difficulties will be overcome, so that the recording of wearable devices will gain sufficient reliability for the recording of ischaemic changes on the ECG.
Eur Heart J. 2022;43(4):271-279. © 2022 Oxford University Press
Copyright 2007 European Society of Cardiology. Published by Oxford University Press. All rights reserved.