ECG 2.0
Visualize atrial activity better, treat better.

Abstract

Keywords: atrial fibrillation; catheter ablation; electrocardiography; follow-up studies; heart atria.

Abstract

Abstract:

This editorial refers to ‘Measures of spatiotemporal organization differentiate persistent from long-standing atrial fibrillation’ by L. Uldry et al., on page 1125

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.

Abstract

Summary

Continuous heart rhythm monitoring elucidated the recurrent and transient nature of recent-onset atrial fibrillation (AF). In theRACE7 ACWAS(1) we showed that a wait-and-see approach (WAS) in patients with recent-onset AF (rate control for symptomrelief followed by delayed cardioversion if needed <48h) allows spontaneous conversion to sinus rhythm in 69% of patients,obviating active cardioversion. Recurrences within one month were seen in 30% of patients in both groups, i.e. the initiallychosen strategy did not affect the recurrence pattern1. Considering the latter, it remains unclear whether cardioversion isneeded at all, especially since cardioversion strategy does not seem to affect behaviour of the arrhythmia over time. Instead ofcardioversion a watchful-waiting rate control strategy may be appropriate as initial strategy. Therefore, we intend to perform amulti-center clinical randomized controlled trial to show non-inferiority of watchful-waiting with rate control versus the WASapproach in terms of prevalence of sinus rhythm at 4 weeks follow-up, using a novel telemonitoring infrastructure(MyDiagnostick®) to guide rate and rhythm control during follow-up. This novel telemonitoring infrastructure may facilitate thewatchful-waiting strategy and obviate the need for cardioversion and reduce costs compared to the delayed rhythm controlWAS strategy.

Summary

Atrial fibrillation (AF) and stroke are major health care problems in Europe. They are most often the clinical expression of atrial cardiomyopathy, which is under-recognised due to the lack of specific diagnostic tools. Multidisciplinary research and stratified approaches are urgently needed to preempt the AF-related threat to healthy ageing in Europe. EU-funded MAESTRIA is a consortium of clinicians, scientists and pharma industrials who are at the forefront of research and medical care of AF and stroke patients. It will create multi-parametric digital tools based on a new generation of biomarkers that integrate artificial intelligence processing and big data from cutting edge imaging, electrocardiography and omics technologies. It will develop novel diagnostic tools and personalised therapies for AF.

Summary

Atrial fibrillation (AF) is the most common sustained cardiac rhythm disorder. It is the leading cause of stroke and doubles cardiovascular morbidity and mortality. More than 5 million people in the EU suffer from AF and it. is estimated that this number will increase to 14–17 million in 2030. Rhythm control therapy of AF shows limited success rates largely related to the lack of mechanism-driven treatment of AF. Individualized therapeutic approaches may offer improvements but require tools to understand the electrophysiological alterations based on easily accessible clinical signs and markers in an individual patient. Our consortium has pioneered the non-invasive assessment of electrophysiological properties of atrial activity during AF and normal sinus rhythm. We showed that electrocardiogram (ECG) features are instrumental in improving prediction of AF treatment outcome and detecting changes associated with AF during sinus rhythm in patients with a history of AF.

The EXACT-IN-AF project aims to develop the next generation of non-invasive AF complexity assessment by introducing the extended ECG: a novel lead configuration that provides and improved image of atrial activity with additional electrodes on the body surface and a transesophageal ECG catheter. The Maastricht University start-up YourRhythmics BV develops a hard- and software solution for recording and the analysis of extended ECGs. We are currently recording these ECGs in patients undergoing electrical cardioversion and in patients scheduled for ablation for AF. Our aim is to develop automated algorithms for advanced ECG feature extraction and build prediction models that can predict recurrence of AF after treatment in these cohorts, and to predict AF incidence in another large cohort of patients without a history of AF. Improved risk assessment of AF incidence and recurrence of AF will facilitate timely and appropriate treatment of AF, thereby reducing AF burden and reducing costs due to AF-related complications and ineffective procedures. The developed algorithms will be incorporated into a decision support tool in the system of YourRhythmics BV and brought to the market to generate sales.

Summary

Rationale: Although there are several individual factors which are known to influence the chances of successful atrial fibrillation (AF) ablation, it remains a challenge to identify patients at risk for ablation failure with satisfactory certainty.
Objectives: To identify predictors of success of AF ablation including clinical factors, AF recurrence patterns, anatomical and electrophysiological characteristics, circulating biomarkers and individual genetic background.
Study design: Prospective registry of patients undergoing AF ablation. Clinical characteristics and results of routine tests are collected. In addition, the following (non-standard) tests are performed: extended surface electrocardiogram (extECG), extended rhythm monitoring, biomarker testing, genetic analysis, questionnaires. In subgroups of patients transesophageal electrocardiogram (TE-ECG), epicardial electroanatomical mapping and/or left atrial appendage (LAA) biopsy is performed.
Study population: Patients aged 18 years and older with documented AF, scheduled for AF ablation.
Main study endpoints: Ablation success after 12 and 24 months, defined as freedom from any episode of documented atrial arrhythmia after the blanking period.