Sparse spectral analysis of atrial fibrillation electrograms

Atrial fibrillation (AF) is a common heart disorder. One of the most prominent hypothesis about its initiation and maintenance considers multiple uncoordinated activation foci inside the atrium. However, the implicit assumption behind all the signal processing techniques used for AF, such as dominant frequency and organization analysis, is the existence of a single regular component in the observed signals. In this paper we take into account the existence of multiple foci, performing a spectral analysis to detect their number and frequencies. In order to obtain a cleaner signal on which the spectral analysis can be performed, we introduce sparsity-aware learning techniques to infer the spike trains corresponding to the activations. The good performance of the proposed algorithm is demonstrated both on synthetic and real data. RESUMEN. Algoritmo basado en técnicas de regresión dispersa para la extracción de las señales cardiacas en pacientes con fibrilación atrial (AF).

Rivaroxabananddabigatraninpatientsundergoing catheter ablation of atrial fibrillation

Aims: The recent availability of the novel oral anticoagulants (NOACs) may have led to a change in the anticoagulation regimens of patients referred to catheter ablation of atrial fibrillation (AF). Preliminary data exist concerning dabigatran, but information regarding the safety and efficacy of rivaroxaban in this setting is currently scarce. Methods: and results Of the 556 consecutive eligible patients (age 61.0 ± 9.6; 74.6% men; 61.2% paroxysmal AF) undergoing AF catheter ablation in our centre (October 2012 to September 2013) and enroled in a systematic standardized 30-day follow-up period: 192 patients were under vitamin K antagonists (VKAs), 188 under rivaroxaban, and 176 under dabigatran. Peri-procedural mortality and significant systemic or pulmonary thromboembolism (efficacy outcome), as well as bleeding events (safety outcome) during the 30 days following the ablation were evaluated according to anticoagulation regimen. During a 12-month time interval, the use of the NOACs in this population rose from <10 to 70%. Overall, the rate of events was low with no significant differences regarding: thrombo-embolic events in 1.3% (VKA 2.1%; rivaroxaban 1.1%; dabigatran 0.6%; P = 0.410); major bleeding in 2.3% (VKA 4.2%; rivaroxaban 1.6%; dabigatran 1.1%; P = 0.112), and minor bleeding 1.4% (VKA 2.1%; rivaroxaban 1.6%; dabigatran 0.6%; P = 0.464). No fatal events were observed. Conclusion: The use of the NOAC in patients undergoing catheter ablation of AF has rapidly evolved (seven-fold) over 1 year. These preliminary data suggest that rivaroxaban and dabigatran in the setting of catheter ablation of AF are efficient and safe, compared with the traditional VKA.

Markers for silent atrial fibrillation in esophageal long-term electrocardiography.

PURPOSE Paroxysmal atrial fibrillation (PAF) often remains undiagnosed. Long-term surface ECG is used for screening, but has limitations. Esophageal ECG (eECG) allows recording high quality atrial signals, which were used to identify markers for PAF. METHODS In 50 patients (25 patients with PAF; 25 controls) an eECG and surface ECG was recorded simultaneously. Partially A-V blocked atrial runs (PBARs) were quantified, atrial signal duration in eECG was measured. RESULTS eECG revealed 1.8‰ of atrial premature beats in patients with known PAF to be PBARs with a median duration of 853ms (interquartile range (IQR) 813-1836ms) and a median atrial cycle length of 366ms (IQR 282-432ms). Even during a short recording duration of 2.1h (IQR 1.2-17.2h), PBARs occurred in 20% of PAF patients but not in controls (p=0.05). Left atrial signal duration was predictive for PAF (72% sensitivity, 80% specificity). CONCLUSIONS eECG reveals partially blocked atrial runs and prolonged left atrial signal duration - two novel surrogate markers for PAF.