Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation.

AIMS: Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. METHODS AND RESULTS: Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7-99.9%], specificity (99.9%; CI: 99.8-100.0%), positive predictive value (99.6%; CI: 99.1-100.0%), and negative predictive value (99.6%; CI: 99.0-100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland-Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. CONCLUSION: Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.

Smartphone-based atrial fibrillation screening in the general population: feasibility and impact on medical treatment.

Aims: The aim of this study is to determine the feasibility, detection rate, and therapeutic implications of large-scale smartphone-based screening for atrial fibrillation (AF). Methods and results: Subjects from the general population in Belgium were recruited through a media campaign to perform AF screening during 8 consecutive days with a smartphone application. The application analyses photoplethysmography traces with artificial intelligence and offline validation of suspected signals to detect AF. The impact of AF screening on medical therapy was measured through questionnaires. Atrial fibrillation was detected in the screened population (n = 60.629) in 791 subjects (1.3%). From this group, 55% responded to the questionnaire. Clinical AF [AF confirmed on a surface electrocardiogram (ECG)] was newly diagnosed in 60 individuals and triggered the initiation of anti-thrombotic therapy in 45%, adjustment of rate or rhythm controlling strategies in 62%, and risk factor management in 17%. In subjects diagnosed with known AF before screening, a positive screening result led to these therapy adjustments in 9%, 39%, and 11%, respectively. In all subjects with clinical AF and an indication for oral anti-coagulation (OAC), OAC uptake increased from 56% to 74% with AF screening. Subjects with clinical AF were older with more co-morbidities compared with subclinical AF (no surface ECG confirmation of AF) (P < 0.001). In subjects with subclinical AF (n = 202), therapy adjustments were performed in only 7%. Conclusion: Smartphone-based AF screening is feasible at large scale. Screening increased OAC uptake and impacted therapy of both new and previously diagnosed clinical AF but failed to impact risk factor management in subjects with subclinical AF.

Detecting Paroxysmal Atrial Fibrillation From an Electrocardiogram in Sinus Rhythm: External Validation of the AI Approach.

BACKGROUND: Atrial fibrillation (AF) may occur asymptomatically and can be diagnosed only with electrocardiography (ECG) while the arrhythmia is present. OBJECTIVES: The aim of this study was to independently validate the approach of using artificial intelligence (AI) to identify underlying paroxysmal AF from a 12-lead ECG in sinus rhythm (SR). METHODS: An AI algorithm was trained to identify patients with underlying paroxysmal AF, using electrocardiographic data from all in- and outpatients from a single center with at least 1 ECG in SR. For patients without AF, all ECGs in SR were included. For patients with AF, all ECGs in SR starting 31 days before the first AF event were included. The patients were randomly allocated to training, internal validation, and testing datasets in a 7:1:2 ratio. In a secondary analysis, the AF prevalence of the testing group was modified. Additionally, the performance of the algorithm was validated at an external hospital. RESULTS: The dataset consisted of 494,042 ECGs in SR from 142,310 patients. Testing the model on the first ECG of each patient (AF prevalence 9.0%) resulted in accuracy of 78.1% (95% CI: 77.6%-78.5%), area under the receiver-operating characteristic curve of 0.87 (95% CI: 0.86-0.87), and area under the precision recall curve (AUPRC) of 0.48 (95% CI: 0.46-0.50). In a low-risk group (AF prevalence 3%), the AUPRC decreased to 0.21 (95% CI: 0.18-0.24). In a high-risk group (AF prevalence 30%), the AUPRC increased to 0.76 (95% CI: 0.75-0.78). This performance was robust when validated in an external hospital. CONCLUSIONS: The approach of using an AI-enabled electrocardiographic algorithm for the identification of patients with underlying paroxysmal AF from ECGs in SR was independently validated.

Reduced Left Atrial Appendage Flow Is Associated With Future Atrial Fibrillation After Cryptogenic Stroke.

BACKGROUND: Hemostasis within the left atrial appendage (LAA) is a common cause of stroke, especially in patients with atrial fibrillation (AF). Although LAA flow provides insights into LAA function, its potential for predicting AF has yet to be established. The aim of this study was to explore whether LAA peak flow velocities early after cryptogenic stroke are associated with future AF on prolonged rhythm monitoring. METHODS: A total of 110 patients with cryptogenic stroke were consecutively enrolled and underwent LAA pulsed-wave Doppler flow assessment using transesophageal echocardiography within the early poststroke period. Velocity measurements were analyzed offline by an investigator blinded to the results. Prolonged rhythm monitoring was conducted on all participants via 7-day Holter and implantable cardiac monitoring devices, with follow-up conducted over a period of 1.5 years to determine the incidence of AF. The end point of AF was defined as irregular supraventricular rhythm with variable RR interval and no detectable P waves lasting ≥30 sec during rhythm monitoring. RESULTS: During a median follow-up period of 539 days (interquartile range, 169-857 days), 42 patients (38%) developed AF, with a median time to AF diagnosis of 94 days (interquartile range, 51-487 days). Both LAA filling velocity and LAA emptying velocity (LAAev) were lower in patients with AF (44.3 ± 14.2 and 50.7 ± 13.3 cm/s, respectively) compared with patients without AF (59.8 ± 14.0 and 76.8 ± 17.3 cm/sec, respectively; P < .001 for both). LAAev was most strongly associated with future AF, with an area under the receiver operating characteristic curve of 0.88 and an optimal cutoff value of 55 cm/sec. Age and mitral regurgitation were independent determinants of reduced LAAev. CONCLUSIONS: Impaired LAA peak flow velocities (LAAev < 55 cm/sec) in patients with cryptogenic stroke are associated with future AF. This may facilitate the selection of appropriate candidates for prolonged rhythm monitoring to improve its diagnostic accuracy and implementation.

Patient motivation and adherence to an on-demand app-based heart rate and rhythm monitoring for atrial fibrillation management: data from the TeleCheck-AF project.

AIMS: The aim of this TeleCheck-AF sub-analysis was to evaluate motivation and adherence to on-demand heart rate/rhythm monitoring app in patients with atrial fibrillation (AF). METHODS AND RESULTS: Patients were instructed to perform 60 s app-based heart rate/rhythm recordings 3 times daily and in case of symptoms for 7 consecutive days prior to teleconsultation. Motivation was defined as number of days in which the expected number of measurements (≥3/day) were performed per number of days over the entire prescription period. Adherence was defined as number of performed measurements per number of expected measurements over the entire prescription period.Data from 990 consecutive patients with diagnosed AF [median age 64 (57-71) years, 39% female] from 10 centres were analyzed. Patients with both optimal motivation (100%) and adherence (≥100%) constituted 28% of the study population and had a lower percentage of recordings in sinus rhythm [90 (53-100%) vs. 100 (64-100%), P < 0.001] compared with others. Older age and absence of diabetes were predictors of both optimal motivation and adherence [odds ratio (OR) 1.02, 95% coincidence interval (95% CI): 1.01-1.04, P < 0.001 and OR: 0.49, 95% CI: 0.28-0.86, P = 0.013, respectively]. Patients with 100% motivation also had ≥100% adherence. Independent predictors for optimal adherence alone were older age (OR: 1.02, 95% CI: 1.00-1.04, P = 0.014), female sex (OR: 1.70, 95% CI: 1.29-2.23, P < 0.001), previous AF ablation (OR: 1.35, 95% CI: 1.03-1.07, P = 0.028). CONCLUSION: In the TeleCheck-AF project, more than one-fourth of patients had optimal motivation and adherence to app-based heart rate/rhythm monitoring. Older age and absence of diabetes were predictors of optimal motivation/adherence.

The Potential and Limitations of Mobile Health and Insertable Cardiac Monitors in the Detection of Atrial Fibrillation in Cryptogenic Stroke Patients: Preliminary Results From the REMOTE Trial.

Aim: This paper presents the preliminary results from the ongoing REMOTE trial. It aims to explore the opportunities and hurdles of using insertable cardiac monitors (ICMs) and photoplethysmography-based mobile health (PPG-based mHealth) using a smartphone or smartwatch to detect atrial fibrillation (AF) in cryptogenic stroke and transient ischemic attack (TIA) patients. Methods and Results: Cryptogenic stroke or TIA patients (n = 39) received an ICM to search for AF and were asked to use a blinded PPG-based mHealth application for 6 months simultaneously. They were randomized to smartphone or smartwatch monitoring. In total, 68,748 1-min recordings were performed using PPG-based mHealth. The number of mHealth recordings decreased significantly over time in both smartphone and smartwatch groups (p < 0.001 and p = 0.002, respectively). Insufficient signal quality was more frequently observed in smartwatch (43.3%) compared to smartphone recordings (17.8%, p < 0.001). However, when looking at the labeling of the mHealth recordings on a patient level, there was no significant difference in signal quality between both groups. Moreover, the use of a smartwatch resulted in significantly more 12-h periods (91.4%) that were clinically useful compared to smartphone users (84.8%) as they had at least one recording of sufficient signal quality. Simultaneously, continuous data was collected from the ICMs, resulting in approximately 6,660,000 min of data (i.e., almost a 100-fold increase compared to mHealth). The ICM algorithm detected AF and other cardiac arrhythmias in 10 and 19 patients, respectively. However, these were only confirmed after adjudication by the remote monitoring team in 1 (10%) and 5 (26.3%) patients, respectively. The confirmed AF was also detected by PPG-based mHealth. Conclusion: Based on the preliminary observations, our paper illustrates the potential as well as the limitations of PPG-based mHealth and ICMs to detect AF in cryptogenic stroke and TIA patients in four elements: (i) mHealth was able to detect AF in a patient in which AF was confirmed on the ICM; (ii) Even state-of-the-art ICMs yielded many false-positive AF registrations; (iii) Both mHealth and ICM still require physician revision; and (iv) Blinding of the mHealth results impairs compliance and motivation.

Will Smartphone Applications Replace the Insertable Cardiac Monitor in the Detection of Atrial Fibrillation? The First Comparison in a Case Report of a Cryptogenic Stroke Patient.

Background and Case: This case report exemplifies the clinical application of non-invasive photoplethysmography (PPG)-based rhythm monitoring in the awakening mobile health (mHealth) era to detect symptomatic and asymptomatic paroxysmal atrial fibrillation (AF) in a cryptogenic stroke patient. Despite extensive diagnostic workup, the etiology remains unknown in one out of three ischemic strokes (i.e., cryptogenic stroke). Prolonged cardiac monitoring can reveal asymptomatic atrial fibrillation in up to one-third of this population. This case report describes a cryptogenic stroke patient who received prolonged cardiac monitoring with an insertable cardiac monitor (ICM) as standard of care. In the context of a clinical study, the patient simultaneously monitored his heart rhythm with a PPG-based smartphone application. AF was detected simultaneously on both the ICM and smartphone application after three days of monitoring. Similar AF burden was detected during follow-up (five episodes, median duration of 28 and 34 h on ICM and mHealth, respectively, p = 0.5). The detection prompted the initiation of oral anticoagulation and AF catheter ablation procedure. Conclusion: This is the first report of the cryptogenic stroke patient in whom PPG-based mHealth was able to detect occurrence and burden of the symptomatic and asymptomatic paroxysmal AF episodes with similar precision as ICM. It accentuates the potential role of PPG-based mHealth in prolonged cardiac rhythm monitoring in cryptogenic stroke patients.

The MADIT-ICD benefit score helps to select implantable cardioverter-defibrillator candidates in cardiac resynchronization therapy.

AIMS: The aim of this study is to evaluate whether the MADIT-ICD benefit score can predict who benefits most from the addition of implantable cardioverter-defibrillator (ICD) to cardiac resynchronization therapy (CRT) in real-world patients with heart failure with reduced ejection fraction (HFrEF) and to compare this with selection according to a multidisciplinary expert centre approach. METHODS AND RESULTS: Consecutive HFrEF patients who received a CRT for a guideline indication at a tertiary care hospital (Ziekenhuis Oost-Limburg, Genk, Belgium) between October 2008 and September 2016, were retrospectively evaluated. The MADIT-ICD benefit groups (low, intermediate, and high) were compared with the current multidisciplinary expert centre approach. Endpoints were (i) sustained ventricular tachycardia (VT) or ventricular fibrillation (VF) and (ii) non-arrhythmic mortality. Of the 475 included patients, 165 (34.7%) were in the lowest, 220 (46.3%) in the intermediate, and 90 (19.0%) in the highest benefit group. After a median follow-up of 34 months, VT/VF occurred in 3 (1.8%) patients in the lowest, 9 (4.1%) in the intermediate, and 13 (14.4%) in the highest benefit group (P < 0.001). Vice versa, non-arrhythmic death occurred in 32 (19.4%) in the lowest, 32 (14.6%) in the intermediate, and 3 (3.3%) in the highest benefit group (P = 0.002). The predictive power for ICD benefit was comparable between expert multidisciplinary judgement and the MADIT-ICD benefit score: Uno's C-statistic 0.69 vs. 0.69 (P = 0.936) for VT/VF and 0.62 vs. 0.60 (P = 0.790) for non-arrhythmic mortality. CONCLUSION: The MADIT-ICD benefit score can identify who benefits most from CRT-D and is comparable with multidisciplinary judgement in a CRT expert centre.

Accuracy of Physicians Interpreting Photoplethysmography and Electrocardiography Tracings to Detect Atrial Fibrillation: INTERPRET-AF.

Aims: This study aims to compare the performance of physicians to detect atrial fibrillation (AF) based on photoplethysmography (PPG), single-lead ECG and 12-lead ECG, and to explore the incremental value of PPG presentation as a tachogram and Poincaré plot, and of algorithm classification for interpretation by physicians. Methods and Results: Email invitations to participate in an online survey were distributed among physicians to analyse almost simultaneously recorded PPG, single-lead ECG and 12-lead ECG traces from 30 patients (10 in sinus rhythm (SR), 10 in SR with ectopic beats and 10 in AF). The task was to classify the readings as 'SR', 'ectopic/missed beats', 'AF', 'flutter' or 'unreadable'. Sixty-five physicians detected or excluded AF based on the raw PPG waveforms with 88.8% sensitivity and 86.3% specificity. Additional presentation of the tachogram plus Poincaré plot significantly increased sensitivity and specificity to 95.5% (P < 0.001) and 92.5% (P < 0.001), respectively. The algorithm information did not further increase the accuracy to detect AF (sensitivity 97.5%, P = 0.556; specificity 95.0%, P = 0.182). Physicians detected AF on single-lead ECG tracings with 91.2% sensitivity and 93.9% specificity. Diagnostic accuracy was also not optimal on full 12-lead ECGs (93.9 and 98.6%, respectively). Notably, there was no significant difference between the performance of PPG waveform plus tachogram and Poincaré, compared to a single-lead ECG to detect or exclude AF (sensitivity P = 0.672; specificity P = 0.536). Conclusion: Physicians can detect AF on a PPG output with equivalent accuracy compared to single-lead ECG, if the PPG waveforms are presented together with a tachogram and Poincaré plot and the quality of the recordings is high.

Atrial Fibrillation Population Screening.

Atrial fibrillation (AF) is associated with adverse outcomes. Screening may lead to earlier recognition and treatment of asymptomatic AF. However, most evidence regarding AF applies to clinical AF, with symptoms or electrocardiographic diagnosis. Whether this evidence can be translated toward subclinical AF, without symptoms and detected by novel, more continuous screening devices is uncertain. The diagnostic yield of screening is determined by the screening population, tool, duration and frequency. Longer and more frequent screening in a higher risk population leads to more effective screening. New devices based on photoplethysmography and single-lead electrocardiography increase convenience and the likelihood of cost-effectiveness.

The European TeleCheck-AF project on remote app-based management of atrial fibrillation during the COVID-19 pandemic: centre and patient experiences.

AIMS: TeleCheck-AF is a multicentre international project initiated to maintain care delivery for patients with atrial fibrillation (AF) during COVID-19 through teleconsultations supported by an on-demand photoplethysmography-based heart rate and rhythm monitoring app (FibriCheck®). We describe the characteristics, inclusion rates, and experiences from participating centres according the TeleCheck-AF infrastructure as well as characteristics and experiences from recruited patients. METHODS AND RESULTS: Three surveys exploring centre characteristics (n = 25), centre experiences (n = 23), and patient experiences (n = 826) were completed. Self-reported patient characteristics were obtained from the app. Most centres were academic (64%) and specialized public cardiology/district hospitals (36%). Majority of the centres had AF outpatient clinics (64%) and only 36% had AF ablation clinics. The time required to start patient inclusion and total number of included patients in the project was comparable for centres experienced (56%) or inexperienced in mHealth use. Within 28 weeks, 1930 AF patients were recruited, mainly for remote AF control (31% of patients) and AF ablation follow-up (42%). Average inclusion rate was highest during the lockdown restrictions and reached a steady state at a lower level after easing the restrictions (188 vs. 52 weekly recruited patients). Majority (>80%) of the centres reported no problems during the implementation of the TeleCheck-AF approach. Recruited patients [median age 64 (55-71), 62% male] agreed that the FibriCheck® app was easy to use (94%). CONCLUSION: Despite different health care settings and mobile health experiences, the TeleCheck-AF approach could be set up within an extremely short time and easily used in different European centres during COVID-19.

Diuretic response and effects of diuretic omission in ambulatory heart failure patients on chronic low-dose loop diuretic therapy.

AIMS: To study loop diuretic response and effect of loop diuretic omission in ambulatory heart failure (HF) patients on chronic low-dose loop diuretics. METHODS AND RESULTS: Urine collections were performed on two consecutive days in 40 ambulatory HF patients with 40-80 mg furosemide (day 1 with loop diuretic; day 2 without loop diuretic). Three phases were collected each day: (i) first 6 h; (ii) rest of the day; and (iii) night. On the day of loop diuretic intake, the total natriuresis was 125.9 (86.9-155.0) mmol/24 h and urine output was 1650 (1380-2025) mL/24 h. There was a clear loop diuretic response with a natriuresis of 9.4 (6.7-15.9) mmol/h and a urine output of 117 (83-167) mL/h during the first 6 h, followed by a significant drop in natriuresis and urine output during the rest of the day [2.6 (1.8-4.8) mmol/h and 55 (33-71) mL/h] and night [2.2 (1.6-3.5) mmol/h and 44 (34-73) mL/h]. On day 2, after loop diuretic omission, the natriuresis and urine output remained similarly low the entire day, resulting in a 50% reduction in natriuresis [55.1 (33.5-77.7) mmol/24 h; P < 0.001] and a 31% reduction in urine output [1035 (875-1425) mL/24 h; P < 0.001] compared with the day of loop diuretic intake. CONCLUSION: Patients with HF on chronic loop diuretic treatment still have a clear diuretic response phase, while loop diuretic omission leads to a significant drop in natriuresis and urine output, arguing against routine cessation of low-dose loop diuretics.

Self-Reported Mobile Health-Based Risk Factor and CHA2DS2-VASc-Score Assessment in Patients With Atrial Fibrillation: TeleCheck-AF Results.

INTRODUCTION: The TeleCheck-AF approach is an on-demand mobile health (mHealth) infrastructure incorporating mobile app-based heart rate and rhythm monitoring through teleconsultation. We evaluated feasibility and accuracy of self-reported mHealth-based AF risk factors and CHA2DS2-VASc-score in atrial fibrillation (AF) patients managed within this approach. MATERIALS AND METHODS: Consecutive patients from eight international TeleCheck-AF centers were asked to complete an app-based 10-item questionnaire related to risk factors, associated conditions and CHA2DS2-VASc-score components. Patient's medical history was retrieved from electronic health records (EHR). RESULTS: Among 994 patients, 954 (96%) patients (38% female, median age 65 years) completed the questionnaire and were included in this analysis. The accuracy of self-reported assessment was highest for pacemaker and anticoagulation treatment and lowest for heart failure and arrhythmias. Patients who knew that AF increases the stroke risk, more often had a 100% or ≥80% correlation between EHR- and app-based results compared to those who did not know (27 vs. 14% or 84 vs. 77%, P = 0.001). Thromboembolic events were more often reported in app (vs. EHR) in all countries, whereas higher self-reported hypertension and anticoagulant treatment were observed in Germany and heart failure in the Netherlands. If the app-based questionnaire alone was used for clinical decision-making on anticoagulation initiation, 26% of patients would have been undertreated and 6.1%-overtreated. CONCLUSION: Self-reported mHealth-based assessment of AF risk factors is feasible. It shows high accuracy of pacemaker and anticoagulation treatment, nevertheless, displays limited accuracy for some of the CHA2DS2-VASc-score components. Direct health care professional assessment of risk factors remains indispensable to ensure high quality clinical-decision making.