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.

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.

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.

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.

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.