Left Bundle Branch Area Pacing and Atrioventricular Node Ablation in a Single-Procedure Approach for Elderly Patients with Symptomatic Atrial Fibrillation.

BACKGROUND: Implantation of a permanent pacemaker and atrioventricular (AV) node ablation (pace-and-ablate) is an established approach for rate and symptom control in elderly patients with symptomatic atrial fibrillation (AF). Left bundle branch area pacing (LBBAP) is a physiological pacing strategy that might overcome right ventricular pacing-induced dyssynchrony. In this study, the feasibility and safety of performing LBBAP and AV node ablation in a single procedure in the elderly was investigated. METHODS: Consecutive patients with symptomatic AF referred for pace-and-ablate underwent the treatment in a single procedure. Data on procedure-related complications and lead stability were collected at regular follow-up at one day, ten days and six weeks after the procedure and continued every six months thereafter. RESULTS: 25 patients (mean age 79.2 ± 4.2 years) were included and underwent successful LBBAP. In 22 (88%) patients, AV node ablation and LBBAP were performed in the same procedure. AV node ablation was postponed in two patients due to lead-stability concerns and in one patient on their own request. No complications related to the single-procedure approach were observed with no lead-stability issues at follow-up. CONCLUSIONS: LBBAP combined with AV node ablation in a single procedure is feasible and safe in elderly patients with symptomatic AF.

Atrial fibrillation-specific refinement of the STOP-Bang sleep apnoea screening questionnaire: insights from the Virtual-SAFARI study.

BACKGROUND: Sleep-disordered breathing (SDB) is prevalent in up to 50% of patients referred for atrial fibrillation (AF) catheter ablation (CA). Currently, it remains unclear how to improve pre-selection for SDB screening in patients with AF. AIM: We aimed to (1) assess the accuracy of the STOP-Bang screening questionnaire for detection of SDB within an AF population referred for CA; (2) derive a refined, AF-specific SDB score to improve pre-selection. METHODS: Consecutive AF patients referred for CA without a history of SDB and/or SDB screening were included. Patients were digitally referred to the previously implemented Virtual-SAFARI SDB screening and management pathway including a home sleep test. An apnoea-hypopnoea index (AHI) of  ≥ 15 was interpreted as moderate-to-severe SDB. Logistic regression analysis was used to assess characteristics associated with moderate-to-severe SDB to refine pre-selection for SDB screening. RESULTS: Of 206 included patients, 51% were diagnosed with moderate-to-severe SDB. The STOP-Bang questionnaire performed poorly in detecting SDB, with an area under the receiver operating characteristic curve (AUROC) of 0.647 (95% Confidence-Interval (CI) 0.573-0.721). AF-specific refinement resulted in the BOSS-GAP score. Therein, BMI with cut-off point ≥ 27 kg/m2 and previous stroke or transient ischaemic attack (TIA) were added, while tiredness and neck circumference were removed. The BOSS-GAP score performed better with an AUROC of 0.738 (95% CI 0.672-0.805) in the overall population. CONCLUSION: AF-specific refinement of the STOP-Bang questionnaire moderately improved detection of SDB in AF patients referred for CA. Whether questionnaires bring benefits for pre-selection of SDB compared to structural screening in patients with AF requires further studies. TRIAL REGISTRATION NUMBER: ISOLATION was registered NCT04342312, 13-04-2020.

Rationale and Design of the ISOLATION Study: A Multicenter Prospective Cohort Study Identifying Predictors for Successful Atrial Fibrillation Ablation in an Integrated Clinical Care and Research Pathway.

Introduction: Continuous progress in atrial fibrillation (AF) ablation techniques has led to an increasing number of procedures with improved outcome. However, about 30-50% of patients still experience recurrences within 1 year after their ablation. Comprehensive translational research approaches integrated in clinical care pathways may improve our understanding of the complex pathophysiology of AF and improve patient selection for AF ablation. Objectives: Within the "IntenSive mOlecular and eLectropathological chAracterization of patienTs undergoIng atrial fibrillatiOn ablatioN" (ISOLATION) study, we aim to identify predictors of successful AF ablation in the following domains: (1) clinical factors, (2) AF patterns, (3) anatomical characteristics, (4) electrophysiological characteristics, (5) circulating biomarkers, and (6) genetic background. Herein, the design of the ISOLATION study and the integration of all study procedures into a standardized pathway for patients undergoing AF ablation are described. Methods: ISOLATION (NCT04342312) is a two-center prospective cohort study including 650 patients undergoing AF ablation. Clinical characteristics and routine clinical test results will be collected, as well as results from the following additional diagnostics: determination of body composition, pre-procedural rhythm monitoring, extended surface electrocardiogram, biomarker testing, genetic analysis, and questionnaires. A multimodality model including a combination of established predictors and novel techniques will be developed to predict ablation success. Discussion: In this study, several domains will be examined to identify predictors of successful AF ablation. The results may be used to improve patient selection for invasive AF management and to tailor treatment decisions to individual patients.

A VIRTUAL Sleep Apnoea management pathway For the work-up of Atrial fibrillation patients in a digital Remote Infrastructure: VIRTUAL-SAFARI.

AIMS: In atrial fibrillation (AF) patients, untreated sleep-disordered breathing (SDB) is associated with lower success rates of rhythm control strategies and as such structured SDB testing is recommended. Herein, we describe the implementation of a virtual SDB management pathway in an AF outpatient clinic and examine the utility and feasibility of this new approach. METHODS AND RESULTS: Prospectively, consecutive AF patients accepted for AF catheter ablation procedures without previous diagnosis of SDB were digitally referred to a virtual SDB management pathway and instructed to use WatchPAT-ONE (ITAMAR) for one night. Results were automatically transferred to a virtual sleep laboratory, upon which a teleconsultation with a sleep physician was planned. Patient experience was measured using surveys. SDB testing was performed in 119 consecutive patients scheduled for AF catheter ablation procedures. The median time from digital referral to finalization of the sleep study report was 18 [11-24] days. In total, 65 patients (55%) were diagnosed with moderate-to-severe SDB. Patients with SDB were prescribed more cardiovascular drugs and had higher body mass indices (BMI, 29 ± 3.3 vs. 27 ± 4.4kg/m2, P < 0.01). Patients agreed that WatchPAT-ONE was easy to use (91%) and recommended future use of this virtual pathway in AF outpatient clinics (86%). Based on this remote SDB testing, SDB treatment was recommended in the majority of patients. CONCLUSION: This novel virtual AF management pathway allowed remote SDB testing in AF outpatient clinics with a short time to diagnosis and high patient satisfaction. Structured SDB testing results in a high detection of previously unknown SDB in AF patients scheduled for AF ablation.

Clinical utility of rhythm control by electrical cardioversion to assess the association between self-reported symptoms and rhythm status in patients with persistent atrial fibrillation.

BACKGROUND: The best strategy to assess the association between symptoms and rhythm status (symptom-rhythm correlation) in patients with atrial fibrillation (AF) remains unclear. We aimed to determine the clinical utility of rhythm control by electrical cardioversion (ECV) to assess symptom-rhythm correlation in patients with persistent AF. METHODS: We used ECV to examine symptom-rhythm correlation in 81 persistent AF patients. According to current clinical practice, the presence of self-reported symptoms before ECV and at the first outpatient clinic follow-up visit (within 1-month) was assessed to determine the prevalence of a symptom-rhythm correlation (defined as self-reported symptoms present during AF and absent in sinus rhythm or absent in AF and yet relief during sinus rhythm). In addition, we evaluated symptom patterns around ECV. RESULTS: Only in 18 patients (22%), a symptom-rhythm correlation could be documented. Twenty-eight patients (35%) did not show any symptom-rhythm correlation and 35 patients (43%) had an unevaluable symptom-rhythm correlation as these patients were in symptomatic AF both at baseline and at the first outpatient AF clinic follow-up visit. Importantly, self-reported symptom patterns around ECV were intra-individually variable in 10 patients (12%) without symptom-rhythm correlation (of which 9 patients (11%) had AF recurrence) and in 2 patients (2%) with an unevaluable symptom-rhythm correlation. CONCLUSIONS: In patients with persistent AF, symptom assessment around rhythm control by ECV, once before ECV and once within 1-month follow-up, rarely identifies a symptom-rhythm correlation and often suggests changes in symptom pattern. Better strategies are needed to assess symptom-rhythm correlation in patients with persistent AF.

A novel framework for noninvasive analysis of short-term atrial activity dynamics during persistent atrial fibrillation.

ECG-based representation of atrial fibrillation (AF) progression is currently limited. We propose a novel framework for a more sensitive noninvasive characterization of the AF substrate during persistent AF. An atrial activity (AA) recurrence signal is computed from body surface potential map (BSPM) recordings, and a set of characteristic indices is derived from it which captures the short- and long-term recurrent behaviour in the AA patterns. A novel measure of short- and long-term spatial variability of AA propagation is introduced, to provide an interpretation of the above indices, and to test the hypothesis that the variability in the oscillatory content of AA is due mainly to a spatially uncoordinated propagation of the AF waveforms. A simple model of atrial signal dynamics is proposed to confirm this hypothesis, and to investigate a possible influence of the AF substrate on the short-term recurrent behaviour of AA propagation. Results confirm the hypothesis, with the model also revealing the above influence. Once the characteristic indices are normalized to remove this influence, they show to be significantly associated with AF recurrence 4 to 6 weeks after electrical cardioversion. Therefore, the proposed framework improves noninvasive AF substrate characterization in patients with a very similar substrate. Graphical Abstract Schematic representation of the proposed framework for the noninvasive characterization of short-term atrial signal dynamics during persistent AF. The proposed framework shows that the faster the AA is propagating, the more stable its propagation paths are in the short-term (larger values of Speed in the bottom right plot should be interpreted as lower speed of propagation of the corresponding AA propagation patters).

The electrocardiogram as a predictor of successful pharmacological cardioversion and progression of atrial fibrillation.

Aims: Non-invasive characterization of atrial fibrillation (AF) substrate complexity based on the electrocardiogram (ECG) may improve outcome prediction in patients receiving rhythm control therapies for AF. Multiple parameters to assess AF complexity and predict treatment outcome have been suggested. A comparative study of the predictive performance of complexity parameters on response to therapy and progression of AF in a large patient population is needed to standardize non-invasive analysis of AF. Methods and results: A large variety of ECG complexity parameters were systematically compared in patients with recent onset AF undergoing pharmacological cardioversion (PCV) with flecainide. Parameters were computed on 10-s 12-lead ECGs of 221 patients before drug administration. The ability of ECG parameters to predict successful PCV and progression to persistent AF (mean follow-up 49 months) was evaluated and compared with common clinical predictors. Optimal prediction performance of successful PCV using only one ECG parameter was low, using dominant atrial frequency [lead II, receiver operating area under curve (AUC) 0.66, 95% confidence interval [0.64-0.67]], but the optimal combination of several ECG parameters strongly improved predictive performance (AUC 0.78 [0.76-0.79]). While predictive value of the optimal combination of clinical predictors was low (AUC 0.68 [0.66-0.70], using right atrial volume and weight), adding ECG parameters strongly increased performance (AUC 0.81 [0.79-0.82], P < 0.001). Interestingly, higher dominant frequency and higher f-wave amplitude were associated with increased risk of progression to persistent AF during follow-up. Conclusion: Assessment of AF complexity from 12-lead ECGs significantly improves prediction of successful PCV and progression to persistent AF compared with common clinical and echocardiographic predictors.

Poor anticoagulation relates to extended access times for cardioversion and is associated with long-term major cardiac and cerebrovascular events.

BACKGROUND: Patients undergoing elective electrical cardioversion (ECV) for atrial fibrillation have a temporarily increased risk of thromboembolism. Current guidelines recommend adequate anticoagulation for ≥3 consecutive weeks precardioversion, i.e. consecutive INR values 2.0-3.0 in patients with vitamin K antagonists (VKA). We aimed to evaluate the occurrence and impact of subtherapeutic INRs precardioversion and to study factors associated with these unwanted fluctuations. METHODS: We recruited 346 consecutive patients undergoing elective ECV in the Maastricht University Medical Centre between 2008 and 2013. Predictors of subtherapeutic INR values were identified and incorporated into a logistic regression model. RESULTS: A subtherapeutic INR precardioversion occurred in 55.2% of patients. The only statistically significant predictor was VKA-naivety (Odds Ratio (OR) 4.78, 95% Confidence Interval (CI) 2.67-8.58, p<0.001). In patients with ≥1 subtherapeutic INR precardioversion, time from referral until cardioversion was 91.1±42.8days, compared to 41.7±26.6days (p<0.001) in patients without subtherapeutic INRs. No thromboembolic events occurred <30days after the ECV. Independent predictors for the combined endpoint of cardiovascular death, ischemic stroke and the need of blood transfusion (n=30, median follow-up of 374days) were coronary artery disease in the history (OR 3.35, 95%CI 1.54-7.25, p=0.002) and subtherapeutic INR precardioversion (OR 3.64, 95%CI 1.43-9.24, p=0.007). CONCLUSIONS: The use of VKA often results in subtherapeutic INRs precardioversion and is associated with a significant delay until cardioversion, especially in patients with recent initiation of VKA therapy. Furthermore, subtherapeutic INR levels prior to ECV are associated with the combined endpoint of cardiovascular death, ischemic stroke and the need of blood transfusion.

P-wave complexity in normal subjects and computer models.

BACKGROUND: P waves reported in electrocardiology literature uniformly appear smooth. Computer simulation and signal analysis studies have shown much more complex shapes. OBJECTIVE: We systematically investigated P-wave complexity in normal volunteers using high-fidelity electrocardiographic techniques without filtering. METHODS: We recorded 5-min multichannel ECGs in 16 healthy volunteers. Noise and interference were reduced by averaging over 300 beats per recording. In addition, normal P waves were simulated with a realistic model of the human atria. RESULTS: Measured P waves had an average of 4.1 peaks (range 1-10) that were reproducible between recordings. Simulated P waves demonstrated similar complexity, which was related to structural discontinuities in the computer model of the atria. CONCLUSION: The true shape of the P wave is very irregular and is best seen in ECGs averaged over many beats.

Atrial Fibrillation Complexity Parameters Derived From Surface ECGs Predict Procedural Outcome and Long-Term Follow-Up of Stepwise Catheter Ablation for Atrial Fibrillation.

BACKGROUND: The success rate of catheter ablation for persistent atrial fibrillation (AF) is still far from satisfactory. Identification of patients who will benefit from ablation is highly desirable. We investigated the predictive value of noninvasive AF complexity parameters derived from standard 12-lead ECGs for AF termination and long-term success of catheter ablation and compared them with clinical predictors. METHODS AND RESULTS: The study included a training (93 patients) and a validation set (81 patients) of patients with persistent AF undergoing stepwise radiofrequency ablation. In the training set AF terminated in 81% during catheter ablation, 77% were in sinus rhythm after 6 years and multiple ablations. ECG-derived complexity parameters were determined from a baseline 10-s 12-lead ECG. Prediction of AF termination was similar using only ECG (cross-validated mean area under the curve [AUC], 0.76±0.15) or only clinical parameters (mean AUC, 0.75±0.16). The combination improved prediction to a mean AUC of 0.79±0.13. Using a combined model of ECG and clinical parameters, sinus rhythm at long-term follow-up could be predicted with a mean AUC of 0.71±0.12. In the validation set AF terminated in 57%, 61% were in sinus rhythm after 4.6 years. The combined models predicted termination with an AUC of 0.70 and sinus rhythm at long-term follow-up with an AUC of 0.61. Overall, fibrillation-wave amplitude provided the best rhythm prediction. CONCLUSIONS: The predictive performance of ECG-derived AF complexity parameters for AF termination and long-term success of catheter ablation in patients with persistent AF is at least as good as known clinical predictive parameters, with fibrillation-wave amplitude as the best predictor.

Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation.

BACKGROUND: Electrical cardioversion (ECV) is one of the rhythm control strategies in patients with persistent atrial fibrillation (AF). Unfortunately, recurrences of AF are common after ECV, which significantly limits the practical benefit of this treatment in patients with AF. OBJECTIVES: The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors. METHODS: We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV. RESULTS: During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG. CONCLUSION: ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor.

Impact of hybrid procedure on P wave duration for atrial fibrillation ablation.

AIM: Hybrid procedure (HP) involves epicardial isolation of pulmonary vein and posterior wall of left atrium, and endocardial checking of lesions and touchups (if needed). We aimed at observing the effect of hybrid procedure on P wave duration (PWD), calculated automatically from surface ECG leads at start and end of HP, and also for relationship to atrial fibrillation (AF) recurrence at 9 months. METHODS: Forty-one patients (32 male; mean age, 58.4 ± 9.5 years) underwent HP, as first ever ablation. A new automated method was used for P wave segmentation and PWD estimation from recognizable P waves in ECG lead I or II before and after HP, based on fitting of each P wave by means of two Gaussian functions. RESULTS: Overall, PWD was significantly decreased after procedure (104.4 ± 25.1 ms vs. 84.7 ± 23.8 ms, p = 0.0151), especially in persistent AF patients (122.4 ± 32.2 ms vs. 85.6 ± 24.5 ms, p = 0.02). PWD preprocedure was significantly higher in persistent than in paroxysmal patients (122.4 ± 32.2 ms vs. 92.5 ± 17.9 ms, p = 0.0383). PWD was significantly decreased after procedure in prior electrical cardioverted patients (106.7 ± 30.5 ms vs. 84.7 ± 23.1 ms, p = 0.0353). After 9-month follow-up of 40 patients, HP-induced PWD decrease was significant for the 12 persistent patients without recurrence (122.4.1 ± 35.3 ms vs. 85.6 ± 22.0 ms, p = 0.0210). CONCLUSION: Preprocedure PWD was higher for persistent than paroxysmal patients. HP reduced PWD significantly. Nine-month follow-up suggests that HP is successful in restoring and maintaining sinus rhythm. To individualize AF therapy, AF type-based selection of patients may be possible before procedure. Automated analysis of PWD from surface ECG is possible.

The ECG as a tool to determine atrial fibrillation complexity.

The use of the ECG for atrial fibrillation (AF) in clinical daily practice is still limited to its diagnosis. Recent research shows however that ECG-derived parameters can also be used to assess the spatiotemporal properties of AF. Specifically, the complexity of the f-waves in the ECG reflects the complexity of the fibrillatory conduction during AF and therefore can be used for quantification of the degree of electrophysiological alterations in the atria. This information might be useful for guiding AF therapy and might form the basis for classification of AF. This review focuses on technical and mathematical aspects of ECG-based atrial complexity assessment and its potential ability to guide treatment strategies.