21 research outputs found
Truths and Lies from the Polysomnography ECG Recording: An Electrophysiologist Perspective
Polysomnography remains the gold standard for diagnosis of Sleep Apnea (SA) and evaluation of the apnea/hypopnea index (AHI) which is used as the primary index of SA severity. The electrocardiogram (typically a single lead) obtained during the polysomnographic study is usually used to report the association between SA and cardiac rhythm disturbances. These findings help in guiding medical decisions but they could also represent a source for confusion. Electrophysiologists are frequently consulted to determine whether interventions need to be taken. We present 2 cases where the ECG during a polysomnography study required the intervention of an electrophysiologist to help with management
Interatrial block in patients with obstructive sleep apnea
Background: Obstructive sleep apnea (OSA) is a common disorder that affects 5% of the
adult North American population. It is associated with atrial arrhythmias and stroke. The
mechanisms of this association remain unclear. The aim to the study was to identify the
factors associated with interatrial block (IAB) among patients with OSA.
Methods: Patients referred for polysomnography were studied. Sleep apnea severity (apnea-hypopnea index [AHI]) was measured in each subject. 12-lead ECGs were scanned and
amplified (× 10); P-wave duration and dispersion were measured using a semi-automatic
caliper. IAB was defined as a P-wave duration ≥ 120 ms.
Results: Data from 180 consecutive patients was examined. Moderate-severe OSA (mean
AHI = 56.2 ± 27.9) was present in 144 (OSA group). The remaining 36 had mild or no OSA
(mean AHI = 5.6 ± 3.6) and were used as controls. Age distribution between the groups did
not differ and there were more males in the OSA group (69.4% vs 47.2%, p = 0.01). Obesity
(78.5% vs 39.4%, p < 0.001) and hypertension (51.4% vs 27.8%, p < 0.01) were more
prevalent in the OSA group. IAB was more prevalent in patients with moderate-severe OSA
(34.7% OSA vs 0% controls, p 30 were
independent predictors of maximum P-wave duration (p = 0.001 and p < 0.001, respectively).
P-wave dispersion was significantly higher in the severe OSA group (14.6 ± 7.5 for OSA, 8.9 ± 3.1 controls, p < 0.001).
Conclusions: Older age and moderate-severe OSA are predictors of IAB. P-wave dispersion
is increased in patients with moderate-severe OSA. This may partly explain the high prevalence
of atrial arrhythmias in patients with OSA. (Cardiol J 2011; 18, 2: 171-175
Regional Dominant Frequency: A New Tool for Wave Break Identification During Atrial Fibrillation
Cardiac mapping systems are based on the time/frequency feature analyses of intracardiac electrograms recorded from individual bipolar/unipolar electrodes. Signals from each electrode are processed independently. Such approaches fail to investigate the interrelationship between simultaneously recorded channels of any given mapping catheter during atrial fibrillation (AF). We introduce a novel signal processing technique that reflects regional dominant frequency (RDF) components. We show that RDF can be used to identify and characterize variation and disorganization in wavefront propagation- wave breaks. The intracardiac electrograms from the left atrium of 15 patients were exported to MATLAB and custom software employed to estimate RDF and wave break rate (WBR). We observed a heterogeneous distribution of both RDF and WBR; the two measures were weakly correlated (0.3; p < 0.001). We identified locations of AF or atrial tachycardia (ATach) termination and later compared offline with RDF and WBR maps. We inspected our novel metrics for associations with AF termination sites. Areas associated with AF termination demonstrated high RDF and low WBR (↑RDF,↓WBR). These sites were present in 14 of 15 patients (mean 2.6 ± 1.2 sites per patient; range, 1–4 sites), 43% situated within the pulmonary veins. In nine patients where AF terminated to sinus rhythm (6) or ATach (3), post-hoc analysis demonstrated all ↑RDF,↓WBR sites were ablated and correlated with AF termination sites. The proposed RDF signal processing tools can be used to identify and quantify wave break, and the combined use of these two novel metrics can aid characterization of AF. Further prospective studies are warranted