Continuous 24-h Photoplethysmogram Monitoring Enables Detection of Atrial Fibrillation

Aim: Atrial fibrillation (AF) detection is challenging because it is often asymptomatic and paroxysmal. We evaluated continuous photoplethysmogram (PPG) for signal quality and detection of AF.Methods: PPGs were recorded using a wrist-band device in 173 patients (76 AF, 97 sinus rhythm, SR) for 24 h. Simultaneously recorded 3-lead ambulatory ECG served as control. The recordings were split into 10-, 20-, 30-, and 60-min time-frames. The sensitivity, specificity, and F1-score of AF detection were evaluated for each time-frame. AF alarms were generated to simulate continuous AF monitoring. Sensitivities, specificities, and positive predictive values (PPVs) of the alarms were evaluated. User experiences of PPG and ECG recordings were assessed. The study was registered in the Clinical Trials database (NCT03507335).Results: The quality of PPG signal was better during night-time than in daytime (67.3 ± 22.4% vs. 30.5 ± 19.4%, p < 0.001). The 30-min time-frame yielded the highest F1-score (0.9536), identifying AF correctly in 72/76 AF patients (sensitivity 94.7%), only 3/97 SR patients receiving a false AF diagnosis (specificity 96.9%). The sensitivity and PPV of the simulated AF alarms were 78.2 and 97.2% at night, and 49.3 and 97.0% during the daytime. 82% of patients were willing to use the device at home.Conclusion: PPG wrist-band provided reliable AF identification both during daytime and night-time. The PPG data’s quality was better at night. The positive user experience suggests that wearable PPG devices could be feasible for continuous rhythm monitoring.

Higher Incidence of Stroke in Severe COVID-19 Is Not Associated With a Higher Burden of Arrhythmias: Comparison With Other Types of Severe Pneumonia

Aims: Thromboembolic events, including stroke, are typical complications of COVID-19. Whether arrhythmias, frequently described in severe COVID-19, are disease-specific and thus promote strokes is unclear. We investigated the occurrence of arrhythmias and stroke during rhythm monitoring in critically ill patients with COVID-19, compared with severe pneumonia of other origins.Methods and Results: This retrospective study included 120 critically ill patients requiring mechanical ventilation in three European tertiary hospitals, including n =60 COVID-19, matched according to risk factors for the occurrence of arrhythmias in n = 60 patients from a retrospective consecutive cohort of severe pneumonia of other origins. Arrhythmias, mainly atrial fibrillation (AF), were frequent in COVID-19. However, when compared with non-COVID-19, no difference was observed with respect to ventricular tachycardias (VT) and relevant bradyarrhythmias (VT 10.0 vs. 8.4 %, p = ns and asystole 5.0 vs. 3.3%, p = ns) with consequent similar rates of cardiopulmonary resuscitation (6.7 vs. 10.0%, p = ns). AF was even more common in non-COVID-19 (AF 18.3 vs. 43.3%, p = 0.003; newly onset AF 10.0 vs. 30.0%, p = 0.006), which resulted in a higher need for electrical cardioversion (6.7 vs. 20.0%, p = 0.029). Despite these findings and comparable rates of therapeutic anticoagulation (TAC), the incidence of stroke was higher in COVID-19 (6.7.% vs. 0.0, p = 0.042). These events also happened in the absence of AF (50%) and with TAC (50%).Conclusions: Arrhythmias were common in severe COVID-19, consisting mainly of AF, yet less frequent than in matched pneumonia of other origins. A contrasting higher incidence of stroke independent of arrhythmias also observed with TAC, seems to be an arrhythmia-unrelated disease-specific feature of COVID-19.

The Influence of Monitoring Strategy on Assessment of Ablation Success and Post-ablation Atrial Fibrillation Burden Assessment: Implications for Practice and Clinical Trial Design

Background: Various non-invasive intermittent rhythm monitoring strategies have been used to assess arrhythmia recurrences in trials of atrial fibrillation (AF) ablation. We determined whether a frequency and duration of non-invasive rhythm monitoring could be identified that accurately detects arrhythmia recurrences and approximates the AF burden derived from continuous monitoring using an implantable cardiac monitor (ICM). Methods: The rhythm history of 346 patients enrolled in the CIRCA-DOSE trial was reconstructed. Using computer simulations, we evaluated event-free survival, sensitivity, negative predictive value, and AF burden of a range of non-invasive monitoring strategies, including those used in contemporary AF ablation trials. Results: A total of 126,290 monitoring days were included in the analysis. At 12 months, 164 patients experienced atrial arrhythmia recurrence as documented by the ICM (1-year event-free survival 52.6%). Most non-invasive monitoring strategies used in AF ablation trials had poor sensitivity for detecting arrhythmia recurrence. Sensitivity increased with the intensity of monitoring, with serial (3) short-duration monitors (24-/48-hour ECG monitors) missing a substantial proportion of recurrences (sensitivity 15.8% [95% confidence interval (CI) 8.9-20.7%] and 24.5% [95% CI 16.2-30.6%], respectively). Serial longer-term monitors (14-day ECG monitors) more closely approximated the gold-standard ICM (sensitivity 64.6% [95% CI 53.6-74.3%]). AF burden derived from short-duration monitors significantly over-estimated the true AF burden in patients with recurrences. Increasing monitoring duration resulted in improved correlation and concordance between non-invasive estimates of the invasive AF burden (R2 = 0.85 and interclass correlation coefficient = 0.91 for serial [3] 14-day ECG monitors vs ICM). Conclusions: Detection of arrhythmia recurrence following ablation is highly sensitive to the monitoring strategy employed, between-trial discrepancies in outcomes may reflect different monitoring protocols. Based on measures of agreement, serial long-term (7-14 day) intermittent monitors accumulating at least 28 days of annual monitoring provide estimates of AF burden comparable to ICM. However, ICMs outperform intermittent monitoring for arrhythmia detection, and should be considered the gold standard for clinical trials.

Automatic Mobile Health Arrhythmia Monitoring for the Detection of Atrial Fibrillation: Prospective Feasibility, Accuracy, and User Experience Study

Background Atrial fibrillation (AF) is the most common tachyarrhythmia and associated with a risk of stroke. The detection and diagnosis of AF represent a major clinical challenge due to AF’s asymptomatic and intermittent nature. Novel consumer-grade mobile health (mHealth) products with automatic arrhythmia detection could be an option for long-term electrocardiogram (ECG)-based rhythm monitoring and AF detection. Objective We evaluated the feasibility and accuracy of a wearable automated mHealth arrhythmia monitoring system, including a consumer-grade, single-lead heart rate belt ECG device (heart belt), a mobile phone application, and a cloud service with an artificial intelligence (AI) arrhythmia detection algorithm for AF detection. The specific aim of this proof-of-concept study was to test the feasibility of the entire sequence of operations from ECG recording to AI arrhythmia analysis and ultimately to final AF detection. Methods Patients (n=159) with an AF (n=73) or sinus rhythm (n=86) were recruited from the emergency department. A single-lead heart belt ECG was recorded for 24 hours. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics and as a reference device in a user experience survey with patients over 65 years of age (high-risk group). Results The heart belt provided a high-quality ECG recording for visual interpretation resulting in 100% accuracy, sensitivity, and specificity of AF detection. The accuracy of AF detection with the automatic AI arrhythmia detection from the heart belt ECG recording was also high (97.5%), and the sensitivity and specificity were 100% and 95.4%, respectively. The correlation between the automatic estimated AF burden and the true AF burden from Holter recording was >0.99 with a mean burden error of 0.05 (SD 0.26) hours. The heart belt demonstrated good user experience and did not significantly interfere with the patient’s daily activities. The patients preferred the heart belt over Holter ECG for rhythm monitoring (85/110, 77% heart belt vs 77/109, 71% Holter, P=.049). Conclusions A consumer-grade, single-lead ECG heart belt provided good-quality ECG for rhythm diagnosis. The mHealth arrhythmia monitoring system, consisting of heart-belt ECG, a mobile phone application, and an automated AF detection achieved AF detection with high accuracy, sensitivity, and specificity. In addition, the mHealth arrhythmia monitoring system showed good user experience. Trial Registration ClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335

Higher incidence of stroke in severe COVID-19 is not associated with a higher burden of arrhythmias: comparison to other types of severe pneumonia

Background Thromboembolic events, including stroke, are typical complications of COVID-19. Whether arrhythmias, frequently described in severe COVID-19, are disease-specific and thus promote strokes is unclear. We investigated the occurrence of arrhythmias, and stroke during rhythm monitoring in critically ill COVID-19, compared to severe pneumonias of other origin. Methods Recruited were 120 critically ill patients requiring mechanical ventilation in three European tertiary hospitals, including n=60 COVID-19, matched according to risk factors for occurrence of arrhythmias to n=60 patients from a retrospective consecutive cohort of severe pneumonias of other origin. Results Arrhythmias, mainly atrial fibrillation (AF), were frequent in COVID-19. However, when compared to nonCOVID-19, no difference was observed with respect to ventricular tachycardias (VT) and relevant bradyarrhythmias (VT 10.0 vs. 8.4%, p=ns and asystole 5.0 vs. 3.3%, p=ns) with consequent similar rates of cardiopulmonary resuscitation (6.7 vs. 10.0% p=ns). AF was even more common in nonCOVID-19 (AF 18.3 vs. 43.3%, p=0.003; newly onset AF 10.0 vs. 30.0%, p=0.006) which resulted in higher need for electrical cardioversion (6.7 vs. 20.0%, p=0.029). Despite these findings and comparable rates of therapeutic anticoagulation (TAC), the incidence of stroke was higher in COVID-19 (6.7.% vs. 0.0, p=0.042). These events happened also in absence of AF (50%) and with TAC (50%). Conclusion Arrhythmias were common in severe COVID-19, consisting mainly of AF, yet less frequent than in matched pneumonias of other origin. A contrasting higher incidence of stroke independent of arrhythmias observed also with TAC, seems to be an arrhythmia-unrelated disease-specific feature of COVID-19. FUNDunding Acknowledgement Type of funding sources: None. Figure 1

Cryptogenic Stroke: Cardiac Rhythm Monitoring as An Indispensable Screening Modality

The prevalence of stroke in Indonesia increased overtime. CS ranges from 15 to 40% from all ischemic strokes. Finding the etiology of ischemic stroke is important to prevent recurrence. AF is predicted as the etiology behind CS. The current recommendation only supports short period of ECG monitoring. However, studies have shown that a higher detection rate can be achieved with longer duration of monitoring. ICM, a diagnostic tool with the highest detection rate, is still considered cost-effective when the calculation takes into account the QALY gained. Digital health tools such as handheld devices and smartwatch ECG have revolutionized the screening of AF however it is still considered as pre-diagnostic and verification is needed to confirm the rhythm generated.