Mobile app-based symptom-rhythm correlation assessment in patients with persistent atrial fibrillation

Background: The assessment of symptom-rhythm correlation (SRC) in patients with persistent atrial fibrillation (AF) is challenging. Therefore, we performed a novel mobile app-based approach to assess SRC in persistent AF.Methods: Consecutive persistent AF patients planned for electrical cardioversion (ECV) used a mobile app to record a 60-s photoplethysmogram (PPG) and report symptoms once daily and in case of symptoms for four weeks prior and three weeks after ECV. Within each patient, SRC was quantified by the SRC-index defined as the sum of symptomatic AF recordings and asymptomatic non-AF recordings divided by the sum of all recordings.Results: Of 88 patients (33% women, age 68 +/- 9 years) included, 78% reported any symptoms during recordings. The overall SRC-index was 0.61 (0.44-0.79). The study population was divided into SRC-index tertiles: low (= 0.73). Patients within the low (vs high) SRC-index tertile had more often heart failure and diabetes mellitus (both 24.1% vs 6.9%). Extrasystoles occurred in 19% of all symptomatic non-AF PPG recordings. Within each patient, PPG recordings with the highest (vs lowest) tertile of pulse rates conferred an increased risk for symptomatic AF recordings (odds ratio [OR] 1.26, 95% coincidence interval [CI] 1.04-1.52) and symptomatic non-AF recordings (OR 2.93, 95% CI 2.16-3.97). Pulse variability was not associated with reported symptoms.Conclusions: In patients with persistent AF, SRC is relatively low. Pulse rate is the main determinant of reported symptoms. Further studies are required to verify whether integrating mobile app-based SRC assessment in current workflows can improve AF management

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

Abstract: 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

Mobile app-based symptom-rhythm correlation assessment in patients with persistent atrial fibrillation

BACKGROUND: The assessment of symptom-rhythm correlation (SRC) in patients with persistent atrial fibrillation (AF) is challenging. Therefore, we performed a novel mobile app-based approach to assess SRC in persistent AF. METHODS: Consecutive persistent AF patients planned for electrical cardioversion (ECV) used a mobile app to record a 60-s photoplethysmogram (PPG) and report symptoms once daily and in case of symptoms for four weeks prior and three weeks after ECV. Within each patient, SRC was quantified by the SRC-index defined as the sum of symptomatic AF recordings and asymptomatic non-AF recordings divided by the sum of all recordings. RESULTS: Of 88 patients (33% women, age 68 ± 9 years) included, 78% reported any symptoms during recordings. The overall SRC-index was 0.61 (0.44-0.79). The study population was divided into SRC-index tertiles: low (<0.47), medium (0.47-0.73) and high (≥0.73). Patients within the low (vs high) SRC-index tertile had more often heart failure and diabetes mellitus (both 24.1% vs 6.9%). Extrasystoles occurred in 19% of all symptomatic non-AF PPG recordings. Within each patient, PPG recordings with the highest (vs lowest) tertile of pulse rates conferred an increased risk for symptomatic AF recordings (odds ratio [OR] 1.26, 95% coincidence interval [CI] 1.04-1.52) and symptomatic non-AF recordings (OR 2.93, 95% CI 2.16-3.97). Pulse variability was not associated with reported symptoms. CONCLUSIONS: In patients with persistent AF, SRC is relatively low. Pulse rate is the main determinant of reported symptoms. Further studies are required to verify whether integrating mobile app-based SRC assessment in current workflows can improve AF management

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

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

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 = 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