Validation of the Ventricular Gradient Comparing Sinus Beats and Ectopic Beats

Author(s):  
Marielle Dik ◽  
Resi M Schoonderwoerd ◽  
Sumche Man ◽  
Arie C Maan ◽  
Cees A Swenne
Keyword(s):  
Author(s):  
Gamze Akkuş ◽  
Yeliz Sökmen ◽  
Mehmet Yılmaz ◽  
Özkan Bekler ◽  
Oğuz Akkuş

Background: We aimed prospectively investigate the laboratory and electrocardiographic parameters (hearth rate, QRS, QT, QTc, Tpe, Tpe/QTc, arrhythmia prevalance) in patients with graves disease before and after antithyroid therapy. Methods: 71 patients (48 female, 23 male), age between 18-50 (mean±SD: 36.48±12.20 ) with GD were included into the study. Patients treated with antithyroid therapy (thionamids and/or surgical therapy) to maintain euthyroid status. Patients were examined in terms of electrocardiographic parameters before and after the treatment. Results: Mean TSH, free thyroxin (fT4) and tri-iodothyrionine (fT3) levels of all patients were 0.005±0.21, 3.27± 1.81, 11.42±7.44, respectively. While 9 patients (group 2) underwent surgical therapy, had suspicious of malignant nodule or large goiter and unresponsiveness to medical treatment; the other patients (n=62, group 1) were treated with medical therapy. Patients with surgical therapy had more increased serum fT4 (p=0.045), anti-thyroglobulin value (p=0.018) and more severe graves orbitopathy (n=0.051) before treatment when compared to medical therapy group. Baseline Tpe duration and baseline Tpe/QTc ratio and frequency of supraventricular ectopic beats were found to be significantly higher in group 2 when compared to group 1 (p=0.00, p=0.005). Otherwise baseline mean heart rate, QRS duration, QTc values of both groups were similar. Although the patients became their euthyroid status, group 2 patients had still suffered from more sustained supraventricular ectopics beats than group 1. Conclusion: Distinct from medical treatment group, surgical treatment group with euthyroidism at least 3 months had still suffered from an arrhythmia (Tpe, Tpe/QTc, supraventricular and ventricular ectopic beats).


2008 ◽  
Vol 295 (2) ◽  
pp. H691-H698 ◽  
Author(s):  
Alex Y. Tan ◽  
Shengmei Zhou ◽  
Byung Chun Jung ◽  
Masahiro Ogawa ◽  
Lan S. Chen ◽  
...  

The purpose of the present study was to determine whether thoracic veins may act as ectopic pacemakers and whether nodelike cells and rich sympathetic innervation are present at the ectopic sites. We used a 1,792-electrode mapping system with 1-mm resolution to map ectopic atrial arrhythmias in eight normal dogs during in vivo right and left stellate ganglia (SG) stimulation before and after sinus node crushing. SG stimulation triggered significant elevations of transcardiac norepinephrine levels, sinus tachycardia in all dogs, and atrial tachycardia in two of eight dogs. Sinus node crushing resulted in a slow junctional rhythm (51 ± 6 beats/min). Subsequent SG stimulation induced 20 episodes of ectopic beats in seven dogs and seven episodes of pulmonary vein tachycardia in three dogs (cycle length 273 ± 35 ms, duration 16 ± 4 s). The ectopic beats arose from the pulmonary vein ( n = 11), right atrium ( n = 5), left atrium ( n = 2), and the vein of Marshall ( n = 2). There was no difference in arrhythmogenic effects of left vs. right SG stimulation (13/29 vs. 16/29 episodes, P = nonsignificant). There was a greater density of periodic acid Schiff-positive cells ( P < 0.05) and sympathetic nerves ( P < 0.05) at the ectopic sites compared with other nonectopic atrial sites. We conclude that, in the absence of a sinus node, thoracic veins may function as subsidiary pacemakers under heightened sympathetic tone, becoming the dominant sites of initiation of focal atrial arrhythmias that arise from sites with abundant sympathetic nerves and periodic acid Schiff-positive cells.


EP Europace ◽  
2020 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
D Tachmatzidis ◽  
D Filos ◽  
I Chouvarda ◽  
A Tsarouchas ◽  
D Mouselimis ◽  
...  

Abstract Background A manually beat-to-beat P-wave analysis has previously revealed the existence of multiple P-wave morphologies in patients with paroxysmal Atrial Fibrillation (AF) while on sinus rhythm, distinguishing them from healthy, AF free patients. Purpose The aim of this study was to investigate the effectiveness of an Automated Beat Exclusion algorithm (ABE) that excludes noisy or ectopic beats, replacing manual beat evaluation during beat-to-beat P-wave analysis, by assessing its effect on inter-rater variability and reproducibility. Methods Beat-to-beat P-wave morphology analysis was performed on 34 ten-minute ECG recordings of patients with a history of AF. Each recording was analyzed independently by two clinical experts for a total of four analysis runs; once with ABE and once again with the manual exclusion of ineligible beats. The inter-rater variability and reproducibility of the analysis with and without ABE were assessed by comparing the agreement of analysis runs with respect to secondary morphology detection, primary morphology ECG template and the percentage of both, as these aspects have been previously used to discriminate PAF patients from controls. Results Comparing ABE to manual exclusion in detecting secondary P-wave morphologies displayed substantial (Cohen"s k = 0.69) to almost perfect (k = 0.82) agreement. Area difference among auto and manually calculated main morphology templates was in every case &lt;5% (p &lt; 0.01) and the correlation coefficient was &gt;0.99 (p &lt; 0.01). Finally, the percentages of beats classified to the primary or secondary morphology per recording by each analysis were strongly correlated, for both main and secondary P-wave morphologies, ranging from ρ=0.756 to ρ=0.940 (picture) Conclusion The use of the ABE algorithm does not diminish inter-rater variability and reproducibility of the analysis. The primary and secondary P-wave morphologies produced by all analyses were similar, both in terms of their template and their frequency. Based on the results of this study, the ABE algorithm incorporated in the beat-to-beat P-wave morphology analysis drastically reduces operator workload without influencing the quality of the analysis. Abstract Figure.


2009 ◽  
Vol 3 (6) ◽  
Author(s):  
Amolak Singh ◽  
Yash Sethi ◽  
Sonya Watkins ◽  
Angela Youtsey ◽  
Angie Thomas
Keyword(s):  

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Chun-Cheng Lin ◽  
Chun-Min Yang

This study developed an automatic heartbeat classification system for identifying normal beats, supraventricular ectopic beats, and ventricular ectopic beats based on normalized RR intervals and morphological features. The proposed heartbeat classification system consists of signal preprocessing, feature extraction, and linear discriminant classification. First, the signal preprocessing removed the high-frequency noise and baseline drift of the original ECG signal. Then the feature extraction derived the normalized RR intervals and two types of morphological features using wavelet analysis and linear prediction modeling. Finally, the linear discriminant classifier combined the extracted features to classify heartbeats. A total of 99,827 heartbeats obtained from the MIT-BIH Arrhythmia Database were divided into three datasets for the training and testing of the optimized heartbeat classification system. The study results demonstrate that the use of the normalized RR interval features greatly improves the positive predictive accuracy of identifying the normal heartbeats and the sensitivity for identifying the supraventricular ectopic heartbeats in comparison with the use of the nonnormalized RR interval features. In addition, the combination of the wavelet and linear prediction morphological features has higher global performance than only using the wavelet features or the linear prediction features.


2013 ◽  
Vol 34 (suppl 1) ◽  
pp. P4933-P4933
Author(s):  
E. Soldati ◽  
A. I. Corciu ◽  
R. De Lucia ◽  
G. Zucchelli ◽  
A. Vannozzi ◽  
...  
Keyword(s):  

2012 ◽  
Vol 50 (7) ◽  
pp. 769-772 ◽  
Author(s):  
Thomas Niederhauser ◽  
Thanks Marisa ◽  
Andreas Haeberlin ◽  
Josef Goette ◽  
Marcel Jacoment ◽  
...  

2011 ◽  
Vol 8 (61) ◽  
pp. 1212-1216 ◽  
Author(s):  
Aslak Tveito ◽  
Glenn Lines ◽  
Ola Skavhaug ◽  
Mary M. Maleckar

The well-organized contraction of each heartbeat is enabled by an electrical wave traversing and exciting the myocardium in a regular manner. Perturbations to this wave, referred to as arrhythmias, can lead to lethal fibrillation if not treated within minutes. One manner in which arrhythmias originate is an ill-fated interaction of the regular electrical signal controlling the heartbeat, the sinus wave, with an ectopic stimulus. It is not fully understood how and when ectopic waves are generated. Based on mathematical models, we show that ectopic beats can be characterized in terms of unstable eigenmodes of the resting state.


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