Early prolonged ambulatory cardiac monitoring in stroke (EPACS): an open-label randomised controlled trial

Intersecting Pathways: The Role of Metabolic Dysregulation, Gastrointestinal Microbiome, and Inflammation in Acute Ischemic Stroke Pathogenesis and Outcomes

Acute ischemic stroke (AIS) remains a major cause of mortality and long-term disability worldwide, driven by complex and multifaceted etiological factors. Metabolic dysregulation, gastrointestinal microbiome alterations, and systemic inflammation are emerging as significant contributors to AIS pathogenesis. This review addresses the critical need to understand how these factors interact to influence AIS risk and outcomes. We aim to elucidate the roles of dysregulated adipokines in obesity, the impact of gut microbiota disruptions, and the neuroinflammatory cascade initiated by lipopolysaccharides (LPS) in AIS. Dysregulated adipokines in obesity exacerbate inflammatory responses, increasing AIS risk and severity. Disruptions in the gut microbiota and subsequent LPS-induced neuroinflammation further link systemic inflammation to AIS. Advances in neuroimaging and biomarker development have improved diagnostic precision. Here, we highlight the need for a multifaceted approach to AIS management, integrating metabolic, microbiota, and inflammatory insights. Potential therapeutic strategies targeting these pathways could significantly improve AIS prevention and treatment. Future research should focus on further elucidating these pathways and developing targeted interventions to mitigate the impacts of metabolic dysregulation, microbiome imbalances, and inflammation on AIS.

Handheld 6-Lead ECG for Early Detection of Acute Inferior Wall ST-T Segment Elevation Myocardial Infarction: HINT-MI Study Design and Rationale

Background: ST-T segment elevation myocardial infarction (STEMI) is a critical condition that requires rapid diagnosis and treatment. Recently, various ECG recording devices have been developed. In this study, we aim to determine the utility of a 6-lead handheld ECG recording device to shorten the time taken for the diagnosis of inferior wall STEMI. Methods and Design: HINT-MI is an investigator-derived, observational, prospective study that will evaluate the ability of a handheld 6-lead ECG device to diagnose acute inferior wall STEMI. Patients who have undergone coronary angiography for STEMI or for other reasons will be enrolled in the study. This study aims to evaluate sensitivity and specificity of a handheld 6-lead ECG device by the level of agreement with a standard 12-lead ECG for diagnosing inferior wall STEMI. Further, we will determine whether the use of the handheld device can reduce the time needed for reperfusion treatment through faster diagnosis. Conclusions: This study aims to investigate the feasibility of a handheld 6-lead ECG device for diagnosing inferior wall STEMI to reduce the time required to diagnose inferior wall STEMI and to allow timely treatment.

The Usefulness of Outpatient Cardiac Telemetry in Patients with Cryptogenic Stroke

Introduction: Atrial fibrillation (AF), apart from non-stenotic supracardiac atherosclerosis and neoplastic disease, is the leading cause of cryptogenic stroke, including embolic stroke of un-determined source (ESUS). The aim of our study was to determine the prevalence of AF in ESUS patients based on 30-day telemetric heart rate monitoring initiated within three months after stroke onset. Another aim was to identify factors that increase the likelihood of detecting subsequent AF among ESUS patients. Material and Methods: patients with first-ever stroke classified as per the ESUS definition were eligible for this study. All patients underwent outpatient 30-day telemetric heart rate monitoring. Results: In the period between 2020 and 2022, 145 patients were included. The mean age of all qualified patients was 54; 40% of eligible patients were female. Six patients (4.14%), mostly male patients (4 vs. 2), were diagnosed with AF within the study period. In each case, the diagnosis related to a patient whose stroke occurred in the course of large vessel occlusion. Episodes of AF were detected between day 1 and 25 after starting ECG monitoring. Out of the analyzed parameters that increase the probability of, A.F.; only supraventricular extrasystoles proved to be an independent factor regarding an increased risk of AF [OR 1.046, CI 95% 1.016-1.071, p-value < 0.01]. Conclusions: The use of telemetry heart rhythm monitoring in an outpatient setting can detect AF in 4% of ESUS patients who have undergone prior diagnostic procedures for cardiogenic embolism. Supraventricular extrasystoles significantly increases the likelihood of AF detection in patients with ESUS within three months following stroke. Comorbid coronary artery disease, diabetes and hypertension, rather than a single-factor clinical burden, increase the likelihood of AF detection in older ESUS patients. ESUS in the course of large vessel occlusion is probably associated with an increased likelihood of cardiogenic embolism.

Identifying the optimal time period for detection of atrial fibrillation after ischaemic stroke and TIA: An updated systematic review and meta-analysis of randomized control trials

BACKGROUND

Atrial fibrillation (AF) is a major risk factor for ischaemic stroke (IS) and transient ischaemic attack (TIA). The timely detection of first-diagnosed or "new" AF (nAF) would prompt a switch from antiplatelets to anticoagulation to reduce the risk of stroke recurrence; however, the optimal timing and duration of rhythm monitoring to detect nAF remains unclear.

AIMS

We searched MEDLINE, PubMed, Cochrane database, and Google Scholar to undertake a systematic review and meta-analysis of randomized controlled trials (RCT) between 2012 and 2023 investigating nAF detection after IS and TIA. Outcome measures were overall detection of nAF (control; (usual care) compared to intervention; (continuous cardiac monitoring >72 h)) and the time period in which nAF detection is highest (0-14 days, 15-90 days, 91-180 days, or 181-365 days). A random-effects model with generic inverse variance weights was used to pool the most adjusted effect measure from each trial.

SUMMARY OF REVIEW

A total of eight RCTs investigated rhythm monitoring after IS, totaling 5820 patients. The meta-analysis of the studies suggested that continuous cardiac monitoring was associated with a pooled odds ratio of 3.81 (95% CI 2.14 to 6.77), compared to usual care (control), for nAF detection. In the time period analysis, the odds ratio for nAF detection at 0-14 days, 15-90 days, 91-180 days, 181-365 days were 1.79 (1.24-2.58); 2.01 (0.63-6.37); 0.98 (0.16-5.90); and 2.92 (1.30-6.56), respectively.

CONCLUSION

There is an almost fourfold increase in nAF detection with continuous cardiac monitoring, compared to usual care. The results also demonstrate two statistically significant time periods in nAF detection; at 0-14 days and 6-12 months following monitoring commencement. These data support the utilization of different monitoring methods to cover both time periods and a minimum of 1 year of monitoring to maximize nAF detection in patients after IS and TIA.

Comparison of continuous 24-hour and 14-day ECG monitoring for the detection of cardiac arrhythmias in patients with ischemic stroke or syncope

BACKGROUND

Previous studies show that using 12-lead electrocardiogram (ECG) or 24-h ECG monitor for the detection of cardiac arrhythmia events in patients with stroke or syncope is ineffective.

HYPOTHESIS

The 14-day continuous ECG patch has higher detection rates of arrhythmias compared with conventional 24-h ECG monitoring in patients with ischemic stroke or syncope.

METHODS

This cross-sectional study of patients with newly diagnosed ischemic stroke or syncope received a 24-h ECG monitoring and 14-day continuous cardiac monitoring patch and the arrhythmia events were measured.

RESULTS

This study enrolled 83 patients with ischemic stroke or syncope. The detection rate of composite cardiac arrhythmias was significantly higher for the 14-day ECG patch than 24-h Holter monitor (69.9% vs. 21.7%, p = .006). In patients with ischemic stroke, the detection rates of cardiac arrhythmias were 63.4% for supraventricular tachycardia (SVT), 7% for ventricular tachycardia (VT), 5.6% for atrial fibrillation (AF), 4.2% for atrioventricular block (AVB), and 1.4% for pause by 14-day ECG patch, respectively. The significant difference in arrhythmic detection rates were found for SVT (45.8%), AF (6%), pause (1.2%), AVB (2.4%), and VT (9.6%) by 14-day ECG patch but not by 24-h Holter monitor in patients with ischemic stroke or syncope.

CONCLUSIONS

A 14-day ECG patch can be used on patients with ischemic stroke or syncope for the early detection of AF or other cardiac arrhythmia events. The patch can be helpful for physicians in planning medical or mechanical interventions of patients with ischemic stroke and occult AF.

Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment

BACKGROUND

Wearable devices may be useful for identification, quantification and characterization, and management of atrial fibrillation (AF). To date, consumer wrist-worn devices for AF detection using photoplethysmography-based algorithms perform only periodic checks when the user is stationary and are US Food and Drug Administration cleared for prediagnostic uses without intended use for clinical decision-making. There is an unmet need for medical-grade diagnostic wrist-worn devices that provide long-term, continuous AF monitoring.

METHODS AND RESULTS

We evaluated the performance of a wrist-worn device with lead-I ECG and continuous photoplethysmography (Verily Study Watch) and photoplethysmography-based convolutional neural network for AF detection and burden estimation in a prospective multicenter study that enrolled 117 patients with paroxysmal AF. A 14-day continuous ECG monitor (Zio XT) served as the reference device to evaluate algorithm sensitivity and specificity for detection of AF in 15-minute intervals. A total of 91 857 intervals were contributed by 111 subjects with evaluable reference and test data (18.3 h/d median watch wear time). The watch was 96.1% sensitive (95% CI, 92.7%-98.0%) and 98.1% specific (95% CI, 97.2%-99.1%) for interval-level AF detection. Photoplethysmography-derived AF burden estimation was highly correlated with the reference device burden (R2=0.986) with a mean difference of 0.8% (95% limits of agreement, -6.6% to 8.2%).

CONCLUSIONS

Continuous monitoring using a photoplethysmography-based convolutional neural network incorporated in a wrist-worn device has clinical-grade performance for AF detection and burden estimation. These findings suggest that monitoring can be performed with wrist-worn wearables for diagnosis and clinical management of AF.

REGISTRATION INFORMATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04546763.

Searching for atrial fibrillation post stroke: is it time for digital devices?

The detection of atrial fibrillation (AF) in patients with cryptogenic stroke (CS) is an essential part of management to limit the risk of recurrence. However, in practice, not all patients who need AF screening are screened, or are screened with significant delays. The disparities of access to examinations, their costs as well as the increasing workload require an evolution of practices both in terms of organization and the type of equipment used. The ubiquity and ease of use of digital devices, together with their evaluation in large population and their expected lower cost, make them attractive as potential alternatives to current equipment at all stages of patient management. However, reliability and accuracy of each digital device for the detection of paroxysmal AF in CS patients should be established before consideration for inclusion in clinical practice. The aim of this short analysis is therefore to review the current practical issues for AF detection in post stroke patients, the potential benefits and issues using digital devices in stroke patients and to position the different digital devices as alternative to standard equipment at each stage of stroke patient pathway. This may help to design future studies for the evaluation of these devices in this context. Under this condition, the time for digital devices to detect AF after stroke seems very close.

The Impact of Heart Rate Variability Monitoring on Preventing Severe Cardiovascular Events

The increase in the incidence of cardiovascular diseases worldwide raises concerns about the urgent need to increase definite measures for the self-determination of different parameters, especially those defining cardiac function. Heart rate variability (HRV) is a non-invasive method used to evaluate autonomic nervous system modulation on the cardiac sinus node, thus describing the oscillations between consecutive electrocardiogram R-R intervals. These fluctuations are undetectable except when using specialized devices, with ECG Holter monitoring considered the gold standard. HRV is considered an independent biomarker for measuring cardiovascular risk and for screening the occurrence of both acute and chronic heart diseases. Also, it can be an important predictive factor of frailty or neurocognitive disorders, like anxiety and depression. An increased HRV is correlated with rest, exercise, and good recovery, while a decreased HRV is an effect of stress or illness. Until now, ECG Holter monitoring has been considered the gold standard for determining HRV, but the recent decade has led to an accelerated development of technology using numerous devices that were created specifically for the pre-hospital self-monitoring of health statuses. The new generation of devices is based on the use of photoplethysmography, which involves the determination of blood changes at the level of blood vessels. These devices provide additional information about heart rate (HR), blood pressure (BP), peripheral oxygen saturation (SpO²), step counting, physical activity, and sleep monitoring. The most common devices that have this technique are smartwatches (used on a large scale) and chest strap monitors. Therefore, the use of technology and the self-monitoring of heart rate and heart rate variability can be an important first step in screening cardiovascular pathology and reducing the pressure on medical services in a hospital. The use of telemedicine can be an alternative, especially among elderly patients who are associated with walking disorders, frailty, or neurocognitive disorders.

Wearable Devices in Cardiovascular Medicine

Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.

Comparison of data quality and monitoring completion rates between clinic and self-applied ECG patches

BACKGROUND

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, direct-to-patient, self-applied ECG patch use has substantially increased. There are limited data comparing clinic with self-applied electrocardiogram (ECG) patches.

OBJECTIVE

The purpose of this study was to compare rates of ECG patch return, percentages of time patches yielded analyzable data (analyzable time), and percentages of prescribed time ECG patches were worn between clinic and self-applied ECG patches before and during COVID-19.

METHODS

A retrospective analysis of patients prescribed an ECG patch during "pre-COVID" (March 1, 2019, through March 1, 2020) and "COVID" (April 4, 2020, through April 1, 2021) years was performed. ECG patch return rates, mean percentages of analyzable time, and mean percentages of prescribed wear time were compared between clinic and self-applied groups.

RESULTS

Among the 29,093 ECG patch prescriptions (19% COVID self-applied), the COVID self-applied group had a lower return rate (90.8%) than did both clinic-applied groups (COVID: 97.1%; pre-COVID: 98.1%; P < .001). Among the 28,048 ECG patches (17.5% self-applied) returned for analysis, the COVID self-applied group demonstrated a lower mean percentage of analyzable time (95.9% ± 8.2%) than did both clinic-applied groups (COVID: 96.6% ± 6.6%; pre-COVID 96.6% ± 7.4%; P < .001). There were no differences in the mean percentage of prescribed wear time between groups (pre-COVID clinic-applied: 96.7% ± 34.3%; COVID clinic-applied: 97.4% ± 39.8%; COVID self-applied: 98.1% ± 52.1%; P = .09).

CONCLUSION

Self-applied ECG patches were returned at a lower rate and had a statistically lower percentage of analyzable time than clinic-applied patches. However, there were no differences between groups in mean percentages of prescribed wear time, and mean percentages of analyzable time were >95% in all groups.

Evaluation of Huawei smart wearables for detection of atrial fibrillation in patients following ischemic stroke: The Liverpool-Huawei stroke study

BACKGROUND

Atrial fibrillation (AF) often remains undetected following stroke. Documenting AF is critical to initiate oral anticoagulation, which has proven benefit in reducing recurrent stroke and mortality in patients with AF. The accuracy and acceptability of using smart wearables to detect AF in patients following stroke is unknown.

METHODS

The aims of the Liverpool-Huawei Stroke Study are to determine the effectiveness, cost-effectiveness and patient and staff acceptability of using Huawei smart wearables to detect AF following ischemic stroke. The study plans to recruit 1,000 adults aged ≥18 years following ischemic stroke from participating hospitals over 12 months. All participants will be asked to wear a Huawei smart band for 4 weeks postdischarge. If participants do not have access to a compatible smartphone required for the study, they will be provided with a smartphone for the 4-week AF monitoring period.

RESULTS

Participants with suspected AF detected by the smart wearables, without previous known AF, will be referred for further evaluation. To determine the effectiveness of the Huawei smart wearables to detect AF, the positive predictive value will be determined. Patient acceptability of using this technology will also be examined. Additional follow-up assessments will be conducted at 6 and 12 months, and clinical outcomes recorded in relation to prevalent and incident AF post-stroke. The study opened for recruitment on May 30, 2022, and is currently open at 4 participating hospitals; the first 106 participants have been recruited. One further hospital is preparing to open for recruitment.

CONCLUSIONS

This prospective study will examine the effectiveness and acceptability of the use of smart wearables in patients following ischemic stroke. This could have important implications for detection of AF and therefore, earlier prophylaxis for recurrent stroke. The study is registered on https://www.isrctn.com/ (Identifier ISRCTN30693819).

Wearables in Cardiovascular Disease

Wearable devices stand to revolutionize the way healthcare is delivered. From consumer devices that provide general health information and screen for medical conditions to medical-grade devices that allow collection of larger datasets that include multiple modalities, wearables have a myriad of potential uses, especially in cardiovascular disorders. In this review, we summarize the underlying technologies employed in these devices and discuss the regulatory and economic aspects of such devices as well as the future implications of their use.

Long-Term Cardiac Monitoring After Embolic Stroke of Undetermined Source: Search Longer, Look Harder

Embolic stroke of undetermined source (ESUS) represents a heterogeneous subgroup of patients with cryptogenic stroke, in which despite an extensive diagnostic workup the cause of stroke remains uncertain. Identifying covert atrial fibrillation among patients with ESUS remains challenging. The increasing use of cardiac implanted electronic devices (CIED), such as pacemakers, implantable defibrillators, and implantable loop recorders (ILR), has provided important information on the burden of subclinical atrial fibrillation. Accumulating evidence indicate that long-term continuous monitoring, especially in selected patients with ESUS, significantly increases the possibility of atrial fibrillation detection, suggesting it may be a cost-effective tool in secondary stroke prevention. This review summarizes available evidence related to the use of long-term cardiac monitoring and the use of implantable cardiac monitoring devices in patients with ESUS.

Systemic immune inflammation index and system inflammation response index are potential biomarkers of atrial fibrillation among the patients presenting with ischemic stroke

Background

Chronic inflammatory disorders in atrial fibrillation (AF) contribute to the onset of ischemic stroke. Systemic immune inflammation index (SIII) and system inflammation response index (SIRI) are the two novel and convenient measurements that are positively associated with body inflammation. However, little is known regarding the association between SIII/SIRI with the presence of AF among the patients with ischemic stroke.

Methods

A total of 526 ischemic stroke patients (173 with AF and 353 without AF) were consecutively enrolled in our study from January 2017 to June 2019. SIII and SIRI were measured in both groups. Logistic regression analysis was used to analyse the potential association between SIII/SIRI and the presence of AF. Finally, the correlation between hospitalization expenses, changes in the National Institutes of Health Stroke Scale (NIHSS) scores and SIII/SIRI values were measured.

Results

In patients with ischemic stroke, SIII and SIRI values were significantly higher in AF patients than in non-AF patients (all p < 0.001). Moreover, with increasing quartiles of SIII and SIRI in all patients, the proportion of patients with AF was higher than that of non-AF patients gradually. Logistic regression analyses demonstrated that log-transformed SIII and log-transformed SIRI were independently associated with the presence of AF in patients with ischemic stroke (log-transformed SIII: odds ratio [OR]: 1.047, 95% confidence interval CI = 0.322–1.105, p = 0.047; log-transformed SIRI: OR: 6.197, 95% CI = 2.196–17.484, p = 0.001). Finally, a positive correlation between hospitalization expenses, changes in the NIHSS scores and SIII/SIRI were found, which were more significant in patients with AF (all p < 0.05).

Conclusions

Our study suggests SIII and SIRI are convenient and effective measurements for predicting the presence of AF in patients with ischemic stroke. Moreover, they were correlated with increased financial burden and poor short-term prognosis in AF patients presenting with ischemic stroke.

European Stroke Organisation (ESO) guideline on screening for subclinical atrial fibrillation after stroke or transient ischaemic attack of undetermined origin

We aimed to provide practical recommendations for the screening of subclinical atrial fibrillation (AF) in patients with ischaemic stroke or transient ischaemic attack (TIA) of undetermined origin. These guidelines are based on the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. Five relevant Population, Intervention, Comparator, Outcome questions were defined by a multidisciplinary module working group (MWG).

Longer duration of cardiac rhythm monitoring increases the detection of subclinical AF, but the optimal monitoring length is yet to be defined. We advise longer monitoring to increase the rate of anticoagulation, but whether longer monitoring improves clinical outcomes needs to be addressed. AF detection does not differ from in- or out-patient ECG-monitoring with similar monitoring duration, so we consider it reasonable to initiate in-hospital monitoring as soon as possible and continue with outpatient monitoring for more than 48h. Although insertable loop recorders (ILR) increase AF detection based on their longer monitoring duration, comparison with non-implantable ECG devices for similar monitoring time is lacking. We suggest the use of implantable devices, if feasible, for AF detection instead of non- implantable devices to increase the detection of subclinical AF. There is weak evidence of a useful role for blood, ECG, and brain imaging biomarkers for the identification of patients at high risk of AF. In patients with patent foramen ovale, we found insufficient evidence from RCT, but prolonged cardiac monitoring in patients >55 years is advisable for subclinical AF detection. To conclude, in adult patients with ischaemic stroke or TIA of undetermined origin, we recommend longer duration of cardiac rhythm monitoring of more than 48h and if feasible with IRL to increase the detection of subclinical AF.

Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives

Remote monitoring and control of heart function are of primary importance for patient evaluation and management, especially in the modern era of precision medicine and personalized approach. Breaking technological developments have brought to the frontline a variety of smart wearable devices, such as smartwatches, chest patches/straps, or sensors integrated into clothing and footwear, which allow continuous and real-time recording of heart rate, facilitating the detection of cardiac arrhythmias. However, there is great diversity and significant differences in the type and quality of the information they provide, thus impairing their integration into daily clinical practice and the relevant familiarization of practicing physicians. This review will summarize the different types and dominant functions of cardiac smart wearables available in the market. Furthermore, we report the devices certified by official American and/or European authorities and the respective sources of evidence. Finally, we comment pertinent limitations and caveats as well as the potential answers that flow from the latest technological achievements and future perspectives.

NExUS-Heart: Novel examinations using smart technologies for heart health-Data sharing from commercial wearable devices and telehealth engagement in participants with or at risk of atrial fibrillation

Background

Telemedicine and commercial wearable devices capable of detecting atrial fibrillation (AF) have revolutionized arrhythmia care during coronavirus disease 2019. However, not much is known about virtual patient-provider interactions or device sharing behaviors.

Objective

The purpose of this study was to characterize how participants with or at risk of AF are engaging with their providers in the context of telemedicine and using commercially wearable devices to manage their health.

Methods

We developed a survey to describe participant behaviors around telemedicine encounters and commercial wearable device use. The survey was distributed to participants diagnosed with AF or those at risk of AF (as determined by being at least 65 years old and having a CHA₂DS₂-VASc stroke risk score of >2) in the University of Massachusetts Memorial Health Care system.

Results

The survey was distributed to 23,530 patients, and there were 1222 (5.19%) participant responses. Among the participants, 327 (26.8%) had AF and 895 (73.2%) were at risk of AF. Neither device ownership nor device type use differed by AF status. After adjusting for covariates that may influence surveyed participant communication patterns, we found that participants with AF were more likely to share their wearable device-derived data with providers (adjusted odds ratio 1.87; 95% confidence interval 1.02-3.41). Rates of sharing physical activity or sleep data were low for both groups and did not differ by AF status.

Conclusion

Compared with participants at risk of developing AF, those with AF were more likely to share heart rate and rhythm data from their commercial wearable devices with providers. However, both groups had similar rates of sharing physical activity and sleep data, telemedicine engagement, and technology use and ownership.

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

Mobile Cardiac Outpatient Telemetry Patch vs Implantable Loop Recorder in Cryptogenic Stroke Patients in the US - Cost-Minimization Model

Purpose

The aim of this study was to compare costs and outcomes of mobile cardiac outpatient telemetry (MCOT) patch followed by implantable loop recorder (ILR) compared to ILR alone in cryptogenic stroke patients from the US health-care payors’ perspective.

Patients and Methods

A quantitative decision tree cost-minimization simulation model was developed. Eligible patients were 18 years of age or older and were diagnosed with having a cryptogenic stroke, without previously documented atrial fibrillation (AF). All patients were assigned first to one then to the alternative monitoring strategies. Following AF detection, patients were initiated on oral anticoagulants (OAC). The model assessed direct costs for one year attributed to MCOT patch followed by ILR or ILR alone using a monitoring duration of 30 days post-cryptogenic stroke.

Results

In the base case modeling, the MCOT patch arm detected 4.6 more patients with AFs compared to the ILR alone arm in a cohort of 1000 patients (209 vs 45 patients with detected AFs, respectively). Using MCOT patch followed by ILR in half of the patients initially undiagnosed with AF leads to significant cost savings of US$4,083,214 compared to ILR alone in a cohort of 1000 patients. Cost per patient with detected AF was significantly lower in the MCOT patch arm $29,598 vs $228,507 in the ILR only arm.

Conclusion

An initial strategy of 30-day electrocardiogram (ECG) monitoring with MCOT patch in diagnosis of AF in cryptogenic stroke patients realizes significant cost-savings compared to proceeding directly to ILR only. Almost 8 times lower costs were achieved with improved detection rates and reduction of secondary stroke risk due to new anticoagulant use in subjects with MCOT patch detected AF. These results strengthen emerging recommendations for prolonged ECG monitoring in secondary stroke prevention.

The Box: Methods and Results of a Real World Experience of mHealth Implementation in Clinical Practice

Background

Mobile health (mHealth) is an emerging field of scientific interest worldwide. Potential benefits include increased patient engagement, improved clinical outcomes, and reduced health care costs. However, mHealth is often studied in projects or trials, and structural implantation in clinical practice is less common.

Objective

The purpose of this paper is to outline the design of the Box and its implementation and use in an outpatient clinic setting. The impact on logistical outcomes and patient and provider satisfaction is discussed.

Methods

In 2016, an mHealth care track including smartphone-compatible devices, named the Box, was implemented in the cardiology department of a tertiary medical center in the Netherlands. Patients with myocardial infarction, rhythm disorders, cardiac surgery, heart failure, and congenital heart disease received devices to measure daily weight, blood pressure, heart rate, temperature, and oxygen saturation. In addition, professional and patient user comments on the experience with the care track were obtained via structured interviews.

Results

From 2016 to April 2020, a total of 1140 patients were connected to the mHealth care track. On average, a Box cost €350 (US $375), not including extra staff costs. The median patient age was 60.8 (IQR 52.9-69.3) years, and 73.59% (839/1140) were male. A median of 260 (IQR 105-641) measurements was taken on a median of 189 (IQR 98-372) days. Patients praised the ease of use of the devices and felt more involved with their illness and care. Professionals reported more productive outpatient consultations as well as improved insight into health parameters such as blood pressure and weight. A feedback loop from the hospital to patient to focus on measurements was commented as an important improvement by both patients and professionals.

Conclusions

In this study, the design and implementation of an mHealth care track for outpatient follow-up of patients with various cardiovascular diseases is described. Data from these 4 years indicate that mHealth is feasible to incorporate in outpatient management and is generally well-accepted by patients and providers. Limitations include the need for manual measurement data checks and the risk of data overload. Moreover, the tertiary care setting in which the Box was introduced may limit the external validity of logistical and financial end points to other medical centers. More evidence is needed to show the effects of mHealth on clinical outcomes and on cost-effectiveness.

Comparative Clinical Effectiveness of Population-Based Atrial Fibrillation Screening Using Contemporary Modalities: A Decision-Analytic Model

Background Atrial fibrillation (AF) screening is endorsed by certain guidelines for individuals aged ≥65 years. Yet many AF screening strategies exist, including the use of wrist-worn wearable devices, and their comparative effectiveness is not well-understood. Methods and Results We developed a decision-analytic model simulating 50 million individuals with an age, sex, and comorbidity profile matching the United States population aged ≥65 years (ie, with a guideline-based AF screening indication). We modeled no screening, in addition to 45 distinct AF screening strategies (comprising different modalities and screening intervals), each initiated at a clinical encounter. The primary effectiveness measure was quality-adjusted life-years, with incident stroke and major bleeding as secondary measures. We defined continuous or nearly continuous modalities as those capable of monitoring beyond a single time-point (eg, patch monitor), and discrete modalities as those capable of only instantaneous AF detection (eg, 12-lead ECG). In total, 10 AF screening strategies were effective compared with no screening (300-1500 quality-adjusted life-years gained/100 000 individuals screened). Nine (90%) effective strategies involved use of a continuous or nearly continuous modality such as patch monitor or wrist-worn wearable device, whereas 1 (10%) relied on discrete modalities alone. Effective strategies reduced stroke incidence (number needed to screen to prevent a stroke: 3087-4445) but increased major bleeding (number needed to screen to cause a major bleed: 1815-4049) and intracranial hemorrhage (number needed to screen to cause intracranial hemorrhage: 7693-16 950). The test specificity was a highly influential model parameter on screening effectiveness. Conclusions When modeled from a clinician-directed perspective, the comparative effectiveness of population-based AF screening varies substantially upon the specific strategy used. Future screening interventions and guidelines should consider the relative effectiveness of specific AF screening strategies.

Quality Improvement in Atrial Fibrillation detection after ischaemic stroke (QUIT-AF)

BACKGROUND

Paroxysmal atrial fibrillation (PAF) is a frequent cause of recurrent stroke but can be difficult to detect because of its episodic and often asymptomatic nature. We sought to improve rate of PAF detection through a quality improvement project (QIP) to deliver early prolonged inpatient cardiac monitoring on the stroke unit (SU).

METHODS

A structured protocol for cardiac monitoring using 5-day event recorders was established. 'In-house' cardiac monitoring was implemented. Performance data on this change in service was analysed prospectively and summary statistics obtained.

RESULTS

One-hundred and two ischaemic stroke (IS) patients undertook 5-day event recorder monitoring. Provision of monitors as an inpatient (IP) increased from 20% (pre-QIP pilot 2018) to 65.7% (during QIP). New AF was detected in 15 patients (14.7% vs 8.6% pre-QIP pilot 2018) with majority of new AF (13 patients; 19%) detected when monitors applied early (IP) after IS.

CONCLUSION

Although this study had a number of limitations, it did demonstrate that early and prolonged non-invasive IP cardiac monitoring could be delivered 'in-house' on the SU and improve AF detection rates.

Impact of Mobile Health Devices for the Detection of Atrial Fibrillation: Systematic Review

Background

Atrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate.

Objective

The goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up—for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient’s chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates.

Methods

Two reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size.

Results

A total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I² of 61.9, and therefore it was decided to not pool the results into a meta-analysis.

Conclusions

Although the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant.

Enhanced detection of cardiac arrhythmias utilizing 14-day continuous ECG patch monitoring

BACKGROUND

To evaluate the performance of a single‑lead, 14-day continuous electrocardiogram (ECG) patch for the detection of arrhythmias compared to conventional 24-h monitoring.

METHODS

This prospective clinical trial enrolled patients suspected of arrhythmias but not diagnosed by 12‑lead ECGs. Each patient underwent a 24-h Holter and 14-day ECG patch simultaneously. Seven types of arrhythmias were classified: supraventricular tachycardia (SVT, repetitive atrial beats >4 beats), irregular SVT without P wave (>4 beats), AF/AFL (irregular SVT without P wave ≥30 s), pause ≥3 s, atrioventricular block (AVB; Mobitz type II, third-degree, two to one or high degree AVB), ventricular tachycardia (VT), and polymorphic VT.

RESULTS

A total of 158 patients were recruited (mean wear time:12.3 ± 3.2 days). The overall arrhythmia detection rate was higher with 14-day ECG patches (59.5%) compared to 24-h Holter (19.0%, P < 0.001). Up to 87.2% of arrhythmias recorded with 14-day ECG patches were not associated with symptoms. The 14-day ECG patch was associated with higher detection rates compared to the 24-h Holter in patients with SVT (52.5% versus 15.8%, P < 0.001), irregular SVT without P wave (12.7% versus 4.4%, P = 0.002), AF/AFL (9.5% versus 3.8%, P = 0.042), and critical arrhythmias (pause ≥3 s, AVB, VT, polymorphic VT) (16.5% versus 2.5%, P < 0.001). The 14-day ECG patch detected more than 2 types of arrhythmias in 5.1% of patients. No serious adverse events in patients wearing the 14-day ECG patch were reported.

CONCLUSIONS

The 14-day ECG patch outperformed 24-h Holter to detect overall, asymptomatic, critical and multiple arrhythmias. It is safe and has the potential to identify individuals with hidden arrhythmias, especially those with critical arrhythmias.

Newer Diagnostic and Cost-Effective Ways to Identify Asymptomatic Atrial Fibrillation for the Prevention of Stroke

Atrial fibrillation (Afib) is the most common and underestimated cardiac arrhythmia with a lifetime risk of >35% after the age of 55 years and the risk continues to rise exponentially. Afib leads to stasis of blood within the atria allowing clot formation and increasing the risk for systemic embolization leading to strokes. Outcomes due to Afib can improve significantly with appropriate treatment. Thus, the need for convenient, well-tolerated, cost-effective cardiac monitoring for Afib is needed. The study aims to evaluate the various newer devices and compare them with traditional Holter monitoring, keeping diagnostic yield, cost-effectiveness, and patients' convenience in mind. Though Holter monitoring is simple and non-expensive, it has major limitations including limited recording capacity, inability for real-time recordings, and inconvenience to patients. Zio Patch (iRhythm Technologies, Inc; San Francisco, CA) and other loop recording devices are patient-friendly, inexpensive, and can offer real-time data for longer days. More prospective studies are needed to evaluate the sensitivity, specificity, and the actual number of patients getting benefits from newer devices by diagnosing Afib sooner and start early prevention therapy.

The COVID-19 challenge to cardiac electrophysiologists: optimizing resources at a referral center

Purpose

To describe how a referral center for cardiac electrophysiology (EP) rapidly changed to comply with the ongoing COVID-19 healthcare emergency.

Methods

We present retrospective data about the modification of daily activities at our EP unit, following the pandemic outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Italy. In particular, in the context of a pre-existing “hub-and-spoke” network, we describe how procedure types and volumes have changed in the last 3 months.

Results

Since our institution was selected as a COVID-19 referral center, the entire in-hospital activity was reorganized to assist more than 1000 COVID-positive cases. Only urgent EP procedures, including ventricular tachycardia ablation and extraction of infected devices, were both maintained and optimized to meet the needs of external hospitals. In addition, most of the non-urgent EP procedures were postponed. Finally, following prompt internal reorganization, both outpatient clinics and on-call services underwent significant modification, by integrating telemedicine support whenever applicable.

Conclusion

We presented the fast reorganization of an EP referral center during the ongoing COVID-19 healthcare emergency. Our hub-and-spoke model may be useful for other centers, aiming at a cost-effective management of resources in the context of a global crisis.

Identification of atrial fibrillation in secondary care diabetes and vascular clinics: a pilot study

Aim: To determine the feasibility and utility of the AliveCor® handheld ECG device in screening for asymptomatic atrial fibrillation in high-risk patients attending secondary care clinics. Materials & methods: Patients were recruited from diabetes and vascular outpatient clinics, and the AliveCor device used to store a 30-second ECG recording. Clinical risk stratification systems (CHAD2S2-VASc and HAS-BLED) assessed individual suitability for oral anticoagulation. Results: Atrial fibrillation was detected in 2 of 149 patients (1.3%), with CHA2DS2-VASc-derived annual stroke risk of 4%. Given low bleeding susceptibility (HAS-BLED), oral anticoagulation was strongly indicated. Conclusion: AliveCor technology offers a simple approach to retrieve large volumes of ECG data. A follow-up study with a larger cohort would reinforce the clinical utility of screening this high-risk population.

Fast-Track Long Term Continuous Heart Monitoring in a Stroke Clinic: A Feasibility Study

Background: Paroxysmal atrial fibrillation (PAF) or flutter is prevalent among patients with cryptogenic stroke. The goal of this study was to investigate the feasibility of incorporating a fast-track, long term continuous heart monitoring (LTCM) program within a stroke clinic. Method: We designed and implemented a fast-track LTCM program in our stroke clinics. The instrument that we used for the study was the ZioXT® device from IRhythm™ Technologies. To implement the program, all clinic support staff received training on the skin preparation and proper placement of the device. We prospectively followed every patient who had a request from one of our inpatient or outpatient stroke or neurology providers to receive LTCM. We recorded patients' demographics, the LTCM indication, as well as related quality measures including same-visit placement, wearing time, analyzable time, LTCM application to the preliminary finding time, as well as patients' out of pocket cost. Results: Out of 501 patients included in the study, 467 (93.2%) patients (mean age 65.9 ± 13; men: 48%) received LTCM; and 92.5% of the patients had the diagnosis of stroke or TIA. 93.7% of patients received their LTCM during the same outpatient visit in the stroke clinic. The mean wearing time for LTCM was 12.1 days (out of 14 days). The average analyzable time among our patients was 95.0%. Eighteen (3.9%, 95%CI: 2.4-6.0) patients had at least one episode of PAF that was sustained for more than 30 s. The rate of PAF was 5.9% (95% CI: 3.5-9.2) among patients with the diagnosis of stroke. Out of 467 patients, 392 (84%) had an out-of-pocket cost of < $100. Conclusion: It is feasible to implement a fast-track cardiac monitoring as part of a stroke clinic with proper training of stroke providers, clinic staff, and support from a cardiology team.