Peter Haemers

Aims: Atrial fibrillation (AF) and atrial flutter (AFL) after cardiac surgery are common and associated with adverse outcomes. The increased risk related to AF or AFL may extend beyond discharge. This study aims to determine whether photoplethysmography (PPG)-based smartphone monitoring to detect AF or AFL after hospital discharge following cardiac surgery improves AF management. Methods and results: The intervention group performed 1 min rhythm checks three times daily using a smartphone-based PPG application during 6 weeks after hospitalization for cardiac surgery. The primary outcome involved AF management interventions by independent physicians, including initiation of oral anticoagulation (OAC), direct cardioversion, and up-titration or initiation of antiarrhythmic drugs. The study included 450 patients [mean (SD) age, 64.1 (9.2) years; 96 women (21.3%); 130 patients with AF history (28.9%); median (IQR) CHA2DS2-VASc score, 2 (1–3)], of whom 238 were randomized to PPG-based monitoring and 212 to usual care. AF/AFL was detected with PPG or electrocardiography in 44 patients (18.5%) in the monitoring group and 4 patients (1.9%) in the usual care group (OR 11.8; 95% CI, 4.2–33.3; P < 0.001); these were new detections in, respectively, 22 patients (9.2%) and 1 patient (0.5%) (OR 21.3; 95% CI, 2.9–166.7; P = 0.003). AF management interventions occurred in 24 patients (10.1%) in the monitoring group compared to 5 patients (2.4%) in the usual care group [odds ratio (OR), 5.1; 95% CI, 1.8–14.4; P = 0.002]. Conclusion: In unselected patients discharged home following cardiac surgery, PPG-based smartphone monitoring revealed significantly more AF/AFL which led to significantly more optimization of AF management.

Background: Consumer-oriented wearable devices (CWDs) such as smartphones and smartwatches have gained prominence for their ability to detect atrial fibrillation (AF) through proprietary algorithms using electrocardiography or photoplethysmography (PPG)–based digital recordings. Despite numerous individual validation studies, a direct comparison of interdevice performance is lacking. Objective: This study aimed to evaluate and compare the ability of CWDs to distinguish between sinus rhythm and AF. Methods: Patients exhibiting sinus rhythm or AF were enrolled through a cardiology outpatient clinic. The participants were instructed to perform heart rhythm measurements using a handheld 6-lead electrocardiogram (ECG) device (KardiaMobile 6L), a smartwatch-derived single-lead ECG (Apple Watch), and two PPG-based smartphone apps (FibriCheck and Preventicus) in a random sequence, with simultaneous 12-lead reference ECG as the gold standard. Results: A total of 122 participants were included in the study: median age 69 (IQR 61-77) years, 63.9% (n=78) men, 25% (n=30) with AF, 9.8% (n=12) without prior smartphone experience, and 73% (n=89) without experience in using a smartwatch. The sensitivity to detect AF was 100% for all devices. The specificity to detect sinus rhythm was 96.4% (95% CI 89.5%-98.8%) for KardiaMobile 6L, 97.8% (95% CI 91.6%‐99.5%) for Apple Watch, 98.9% (95% CI 92.5%‐99.8%) for FibriCheck, and 97.8% (95% CI 91.5%‐99.4%) for Preventicus (P=.50). Insufficient quality measurements were observed in 10.7% (95% CI 6.3%-17.5%) of cases for both KardiaMobile 6L and Apple Watch, 7.4% (95% CI 3.9%‐13.6%) for FibriCheck, and 14.8% (95% CI 9.5%‐22.2%) for Preventicus (P=.21). Participants preferred Apple Watch over the other devices to monitor their heart rhythm. Conclusions: In this study population, the discrimination between sinus rhythm and AF using CWDs based on ECG or PPG was highly accurate, with no significant variations in performance across the examined devices.

Aims: Trials on integrated care for atrial fibrillation (AF) showed mixed results in different AF populations using various approaches. The multicentre, randomized AF-EduCare trial evaluated the effect of targeted patient education on unplanned cardiovascular outcomes. Methods and results: Patients willing to participate were randomly assigned to in-person education, online education, or standard care (SC) and followed for minimum 18 months. Education focused on four aspects of integrated AF care: (i) knowledge on AF and oral anticoagulation; (ii) reinforcement of medication adherence; (iii) awareness about risk factors; and (iv) reachability for AF-related questions. The primary endpoint was the composite of cumulative events of unplanned cardiovascular hospitalizations and consultations, emergency department visits for cardiovascular reasons, and cardiovascular death. A total of 1038 patients (69.8 ± 9.2 years) were followed up for 26.9 ± 9.4 months. Education (both in-person and online) significantly improved AF-related knowledge compared to SC (P < 0.001), increased patient awareness about risk factors, led to high medication adherence, and encouraged patients to ask health-related questions. However, in-person education did not show an effect on the primary outcome compared to SC [HR 1.02 (0.91–1.14); P = 0.80] that was also not the case when comparing online education vs. SC [HR 1.18 (0.95–1.46), P = 0.65]. Exploratory subgroup analyses showed a heterogeneous effect over the centres, but a positive impact of in-person education in patients with asymptomatic AF, being 70 years old or younger, and without a history of heart failure. Conclusion: AF-EduCare showed that intensive targeted patient education did not lead to less unplanned cardiovascular events in the AF patient population as a whole, although subgroups might benefit.

Introduction: Postoperative atrial fibrillation (POAF) occurring after cardiac surgery is common and associated with adverse outcomes. Systematic monitoring of POAF beyond discharge is cumbersome. The emergence of photoplethysmography (PPG)-based rhythm monitoring with digital consumer devices could potentially mitigate these hurdles. Selected smartphone applications leveraging this technology have demonstrated excellent usability and accuracy for the detection of atrial fibrillation (AF). However, the impact of PPG-detected POAF on real-life clinical practice remains uncertain. Purpose: To determine whether intermittent PPG-based smartphone rhythm monitoring, after being discharged home following cardiac surgery, impacts AF management. Methods: The SURGICAL-AF 2 study is a pragmatic, investigator-initiated, open-label, multicenter, randomized clinical trial, conducted in three Belgian centers. The intervention group performed one-minute rhythm checks three times daily with a smartphone-based PPG application after hospitalization for cardiac surgery until the first follow-up visit with a cardiologist, scheduled at 21 – 91 days. Rhythm monitoring was not mandated in the usual care group. The primary endpoint was a composite of initiation of oral anticoagulation (OAC), cardioversion, up-titration or initiation of antiarrhythmic drugs (Vaughan-Williams class I or III) or implantation of a cardiac implantable electronic device (CIED). Secondary endpoints were incidence of POAF and actionable POAF, defined as a detection in patients with CHA2DS2-VASc score ≥2 for women or ≥1 for men who are not treated with OAC. Results: Of the 450 patients randomized (238 patients in the intervention group and 212 patients in the usual care group; mean [SD] age, 64.1 [9.2] years; 96 women [21.3%]; 130 patients with AF before inclusion [28.9%]; 103 patients on OAC [22.9%], median [interquartile range] CHA2DS2-VASc score, 2 [1-3]), 98.7% completed the trial. In the intent-to-treat analysis, the primary end point occurred in 24 patients (10.3%) in the intervention group versus 5 patients (2.4%) in the usual care group (odds ratio (OR) 4.7, 95% CI, 1.8 - 12.6; P =.002). POAF was detected in 44 patients (18.8%) in the intervention group and was actionable in 25 patients (10.7%) versus 4 patients (1.9%) in the usual care group and actionable in 2 patients (0.9%). (POAF detection, OR 12.0, 95% CI, 4.2 - 34.5; P < .001; actionable POAF, OR 12.5, 95% CI, 2.9 - 52.6; P < .001) Conclusions: In unselected patients discharged home following cardiac surgery, PPG-based smartphone monitoring revealed significantly more POAF which led to changes in AF management (OAC initiation, rhythm control therapy or CIED insertion). Longer follow-up is needed to determine whether these changes will lead to improved outcomes.

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. 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. 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.

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). 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%. 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. Subjects from the general population were recruited through a media campaign to perform AF screening with a smartphone application. The application analyses photoplethysmography traces with artificial intelligence and offline validation of suspected signals to detect AF. The number needed to screen to detect a new case of AF was 133. When AF is confirmed on a surface ECG, it is referred to as clinical AF. In all subjects with clinical AF and an elevated CHA₂DS₂-VASC score, OAC uptake increased from 56% to 74% with AF screening. Subclinical AF refers to AF that is not confirmed with a surface ECG, OAC uptake in this group increased from 15% to 18%. AF, atrial fibrillation; ECG, electrocardiogram; OAC, oral anti-coagulation; PPG, photoplethysmography.

A 42-year-old man with no prior medical history was hospitalized for an uncomplicated myocarditis. Two weeks after discharge, he was transferred to our centre in an arrhythmic storm. His electrocardiogram showed a broad complex tachycardia with a left bundle branch block (LBBB) pattern very similar to that in sinus rhythm, suggestive of a bundle branch re-entrant ventricular tachycardia (BBR-VT) (Panel A). Cardiac MRI was compatible with active myocarditis with pronounced myocardial oedema. Electrophysiological findings demonstrated the main hallmarks of BBR-VT, a form of ventricular tachycardia that includes both bundles and ventricular septum in its re-entrant circuit. A conduction delay in the His–Purkinje system is necessary to initiate the tachycardia. Interestingly, there was important oedema in the septal region of the left ventricle due to the myocarditis, which could lead to the conduction abnormalities.

Background: Cryoballoon ablation (CRYO) for pulmonary vein isolation (PVI) in atrial fibrillation (AF) has become an established treatment option as alternative for radiofrequency catheter ablation (RFCA). As symptom relief is still the main indication for PVI, quality of life (QoL) is a key outcome parameter. This review summarizes the evidence about the evolution of QoL after CRYO.Methods: A search for clinical studies reporting QoL outcomes after CRYO was performed on PUBMED and COCHRANE. A total of 506 publications were screened and 10 studies met the in‐ and exclusion criteria.Results: All studies considered QoL as a secondary endpoint and reported significant improvement in QoL between baseline and 12 months follow‐up, independent of the QoL instruments used. The effect size of CRYO on QoL was comparable between studies and present in both paroxysmal and persistent AF. Direct comparison between CRYO and RFCA was limited to two studies, there was no difference between ablation modalities after 12 months FU. Two studies in paroxysmal AF reported outcome beyond 12 months follow‐up and QoL improvement was maintained up to 36 months after ablation. There were no long‐term data available for persistent AF.Conclusion: CRYO of AF significantly improves QoL. The scarce amount of data with direct comparison between subgroups limits further exploration. Assessment of QoL should be considered a primary outcome parameter in future trials with long‐term follow‐up.