Dieter Nuyens

Aims: Obesity and atrial fibrillation (AF) are global epidemics, often co-existing and compounding cardiovascular risk. While catheter ablation has emerged as an effective strategy for rhythm control in symptomatic AF, it remains unclear whether obesity modifies its benefit. This post hoc analysis of the CABANA trial investigates the influence of baseline obesity on clinical outcomes after catheter ablation vs. drug therapy in AF patients. Methods and results: A total of 2170 CABANA participants with available body mass index (BMI) were included. Obesity was defined by BMI ≥ 30 kg/m2, and Class II obesity by BMI ≥ 35 kg/m2. Adverse outcomes, AF recurrence, and functional status were analysed using Cox, mixed-effects, and generalized estimating equation models, assessing treatment-by-obesity interactions. Obese patients exhibited higher comorbidity burden, worse baseline functional status, and more persistent AF compared to non-obese counterparts. Higher BMI was associated with increased cardiovascular hospitalization and a higher New York Heart Association functional class. Catheter ablation significantly reduced the risk of AF recurrence and improved symptom burden and functional capacity, irrespective of obesity status. No significant interaction was found between BMI and treatment effect on the primary composite endpoint of cardiovascular hospitalization or all-cause mortality. However, patients with Class II obesity or higher had worse absolute outcomes despite similar relative benefits from ablation. Conclusion: While obesity is associated with worse baseline status and outcomes, it was not shown to significantly alter the relative effectiveness of AF ablation compared to drug therapy. These findings support a multifaceted approach integrating rhythm control with upstream interventions targeting obesity-related atrial remodelling and comorbidity management.

Background and Aims: Detecting subclinical atrial fibrillation (AF) and initiating anticoagulation therapy are critical for secondary stroke prevention after cryptogenic stroke. This study aimed to evaluate the effectiveness of traditional AF risk scores commonly used in clinical practice and compare with an artificial intelligence (AI)-driven ECG-derived AF prediction score. Methods: A retrospective tertiary care center study identified all cryptogenic stroke/TIA patients admitted between 2017-2023 who received an implantable cardiac monitor (ICM). The European Society of Cardiology (ESC)-recommended risk factors and risk score components (i.e.,CHA ₂ DS ₂ -VA, Brown ESUS-AF, and HAVOC) from the 2024 guidelines for AF management, were analyzed using multivariate logistic regression to predict AF within one-year post-ICM insertion. The predictive performance of these risk scores and an AI-driven ECG algorithm for AF detection was assessed and compared. Results: 230 cryptogenic stroke/TIA patients underwent ICM insertion. Only age (OR: 1.033, 95%CI 1.002-1.066) was associated with an increased likelihood of AF detection within one-year post-ICM insertion. The ECG-AI score demonstrated higher predictive power over CHA ₂ DS ₂ -VA and HAVOC (p=.002), and was the only score exceeding an AUROC value of 0.7, but did not outperform Brown ESUS-AF (p=.210). Patients with high scores had a more than two-fold increased likelihood of AF detection (HR: 2.7, 95%CI 1.2-5.8, p=.01). Conclusions: In patients with cryptogenic stroke receiving an ICM, the ECG-AI score showed modest discrimination for AF detection, outperforming CHA ₂ DS ₂ -VA and HAVOC, but not Brown ESUS-AF. Age was the only significant clinical predictor. These findings indicate a possible role for AI-driven ECG analysis in risk stratification.

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.

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.

Sacubitril/valsartan reduced the occurrence of sudden cardiac death in the PARADIGM-HF trial. However, limited information is available about the mechanism.

Introduction: Loss‐of‐function (LoF) mutations in the SCN5A gene cause multiple phenotypes including Brugada Syndrome (BrS) and a diffuse cardiac conduction defect. Markers of increased risk for sudden cardiac death (SCD) in LoF SCN5A mutation carriers are ill defined. We hypothesized that late potentials and fragmented QRS would be more prevalent in SCN5A mutation carriers compared to SCN5A‐negative BrS patients and evaluated risk markers for SCD in SCN5A mutation carriers.Methods: We included all SCN5A loss‐of‐function mutation carriers and SCN5A‐negative BrS patients from our center. A combined arrhythmic endpoint was defined as appropriate ICD shock or SCD.Results: Late potentials were more prevalent in 79 SCN5A mutation carriers compared to 39 SCN5A‐negative BrS patients (66% versus 44%, p = .021), while there was no difference in the prevalence of fragmented QRS. PR interval prolongation was the only parameter that predicted the presence of a SCN5A mutation in BrS (OR 1.08; p < .001). Four SCN5A mutation carriers, of whom three did not have a diagnostic type 1 ECG either spontaneously or after provocation with a sodium channel blocker, reached the combined arrhythmic endpoint during a follow‐up of 44 ± 52 months resulting in an annual incidence rate of 1.37%.Conclusion: LP were more frequently observed in SCN5A mutation carriers, while fQRS was not. In SCN5A mutation carriers, the annual incidence rate of SCD was non‐negligible, even in the absence of a spontaneous or induced type 1 ECG. Therefore, proper follow‐up of SCN5A mutation carriers without Brugada syndrome phenotype is warranted.