Decrease in the Spatial Dispersion at the Termination of Atrial Fibrillation by Intravenous Cibenzoline

Investigational Anti-Atrial Fibrillation Pharmacology and Mechanisms by Which Antiarrhythmics Terminate the Arrhythmia: Where Are We in 2020?

Antiarrhythmic drugs remain the mainstay therapy for patients with atrial fibrillation (AF). A major disadvantage of the currently available anti-AF agents is the risk of induction of ventricular proarrhythmias. Aiming to reduce this risk, several atrial-specific or -selective ion channel block approaches have been introduced for AF suppression, but only the atrial-selective inhibition of the sodium channel has been demonstrated to be valid in both experimental and clinical studies. Among the other pharmacological anti-AF approaches, “upstream therapy” has been prominent but largely disappointing, and pulmonary delivery of anti-AF drugs seems to be promising. Major contradictions exist in the literature about the electrophysiological mechanisms of AF (ie, reentry or focal?) and the mechanisms by which anti-AF drugs terminate AF, making the search for novel anti-AF approaches largely empirical. Drug-induced termination of AF may or may not be associated with prolongation of the atrial effective refractory period. Anti-AF drug research has been largely based on the “suppress reentry” ideology; however, results of the AF mapping studies increasingly indicate that nonreentrant mechanism(s) plays an important role in the maintenance of AF. Also, the analysis of anti-AF drug-induced electrophysiological alterations during AF, conducted in the current study, leans toward the focal source as the prime mechanism of AF maintenance. More effort should be placed on the investigation of pharmacological suppression of the focal mechanisms.

Activation patterns and conduction velocity in posterolateral right atrium during typical atrial flutter using an electroanatomic mapping system

BACKGROUND

To investigate the activation patterns and conduction velocity (CV) in the posterolateral right atrial (RA) wall during typical counterclockwise atrial flutter (AFL) using an electroanatomic mapping system.

METHODS AND RESULTS

During typical AFL in 25 patients, the transverse conduction pattern and CV were classified and calculated. The line blocking transverse conduction was defined by the conduction pattern and double potentials recorded during mapping. There were 3 types (including 2 subtypes) of transverse conduction pattern based on the conduction blocks across the posterolateral RA in a line between the superior and inferior venae cava. Trans-cristal conduction activation in a horizontal direction was seen in all but 4 patients. The CV in the gap area was 0.59+/-0.21 m/s.

CONCLUSIONS

Three types of transverse conduction pattern were observed during trans-ctristal conduction and the trans-ctristal CV was relatively slower than that in other parts of the RA, except for the isthmus.

Spectral Analysis of Atrial Fibrillation Cycle Lengths Comparison Between Fast Fourier Transform Analysis and Autocorrelation Function Analysis Using Multipurpose Physio-Informatic Analysis Software

BACKGROUND

Fast Fourier transform (FFT) analysis is a popular method of spectral analysis of atrial fibrillation cycle lengths (AFCL). Autocorrelation function (ACF) analysis is also available, so the aim of this study was to elucidate the relationship between FFT and ACF analyses in the spectral analysis of AFCLs.

METHODS AND RESULTS

A total of 75 atrial fibrillation (AF) data from 39 patients were subjected to analysis. The dominant frequencies (DFs) from 4 different spectral resolutions of the FFT and peak AFCL from the ACF analysis were compared. In the FFT analysis using rectified signals, the DF was influenced by spectral resolution, no matter how the signals were tapered by the Hanning or Hamming window or filtered with the low-pass filter. There was a significant relationship between the DF from each spectral resolution and the peak AFCL. The DF from the 4,096-point FFT analysis had the strongest relationship to the peak AFCL with the smallest difference, when using 30-s AF data. In a study of the different lengths of the atrial fibrillation data, the DF also had a strong correlation to the peak AFCL with a small difference.

CONCLUSIONS

The peak AFCL obtained from ACF analysis was not of the same quality as that from FFT analysis, but had the same value as the DF from FFT analysis.