Accurate ECG Diagnosis of Atrial Tachyarrhythmias Using Quantitative Analysis: A Prospective Diagnostic and Cost‐Effectiveness Study

Krummen, David E.; Patel, Mitul; Nguyen, Hong Nam; Ho, Gordon; Kazi, Dhruv S.; Clopton, Paul; Holland, M.; Greenberg, S.; Feld, Gregory K.; Faddis, Mitchell N.; Narayan, Sanjiv M.

doi:10.1111/j.1540-8167.2010.01809.x

Cited by 20 publications

(11 citation statements)

References 45 publications

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“…Organization was assessed using loops of atrial activity over time using our described (7,9) and validated (10) method of generating time series of successive correlations to an atrial electrogram. This has the effect of filtering QRS complexes.…”

Section: Methodsmentioning

confidence: 99%

Electrocardiographic spatial loops indicate organization of atrial fibrillation minutes before ablation-related transitions to atrial tachycardia

Baykaner

Trikha

Zaman

et al. 2017

Journal of Electrocardiology

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Background During ablation for atrial fibrillation (AF), it is challenging to anticipate transitions to organized tachycardia (AT). Defining indices of this transition may help to understand fibrillatory conduction and help track therapy. Objective To determine the timescale over which atrial fibrillation (AF) organizes en route to atrial tachycardia (AT) using the ECG referenced to intracardiac electrograms. Methods In 17 AF patients at ablation (58.7±9.6 years; 53% persistent AF) we analyzed spatial loops of atrial activity on the ECG and intracardiac electrograms over successive timepoints. Loops were tracked at precisely 15, 10, 5, 3 and 1 minute prior to defined transitions of AF to AT. Results Organizational indices reliably quantified changes from AF to AT. Spatiotemporal AF organization on the ECG was identifiable at least 15 minutes before AT was established (p=0.02). Conclusions AF shows anticipatory global organization on the ECG minutes before AT is clinically evident. These results offer a foundation to establish when AF therapy is on an effective path, and for a quantitative classification separating AT from AF.

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Section: Methodsmentioning

confidence: 99%

Electrocardiographic spatial loops indicate organization of atrial fibrillation minutes before ablation-related transitions to atrial tachycardia

Baykaner

Trikha

Zaman

et al. 2017

Journal of Electrocardiology

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“…where Â i+u i ,n = (Â − (Â i,n + Â u i ,n ))mod (2 ). The QT interval includes both ventricular depolarization and repolarization.…”

Section: Tq Interval Detection With Particle Filtermentioning

confidence: 99%

“…To further analyze our algorithm, we used the synthetic ECG model in (2) to generate 50 realizations of AT and AFL signals. The sampling frequency was set to 200 Hz, mean heart rate to 150 bpm, standard deviation of heart rate to 1 bpm, and LF/HF ratio to 0.5.…”

Section: Analysis With Synthesized Ecg Signalsmentioning

confidence: 99%

“…The atrial tachyarrythmias atrial flutter (AFL), atrial tachycardia (AT), and atrial fibrillation (AF) represent the most common class of heart rhythm disorders presenting to medical attention [1][2]. Many algorithms have been developed to detect AF and can be categorized as being based on RR interval (RRI) variability [3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Atrial flutter and atrial tachycardia detection using Bayesian approach with high resolution time–frequency spectrum from ECG recordings

Lee

McManus

Bourrell

et al. 2013

Biomedical Signal Processing and Control

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“…At times, despite the regular atrial activity in AFL and AT due to block in the AV node, specially, at high rates the ventricular activity is not regular and the surface ECG can mimic AF. As a result the differentiation between AF and AFL/AT can be a persistent challenge in ECG based diagnosis of atrial arrhythmias, especially when looking at brief periods of surface ECG [2]. Atrial flutter can represent itself with variable RR intervals [3].…”

Section: Introductionmentioning

confidence: 99%

Atrial fibrillation observed on surface ECG can be atrial flutter or atrial tachycardia

Ghafoori

Angel²,

Dosdall

et al. 2018

Journal of Electrocardiology

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Background: Differentiating between atrial fibrillation (AF) and atrial tachycardia (AT) or atrial flutter (AFL) on surface ECG can be challenging. The same problem arises in animal models of AF, in which atrial arrhythmias are induced by pacing or pharmacological intervention with the goal of making mechanistic determinations. Some of these induced arrhythmias can be AFL or AT, even though it might appear as AF on the body-surface ECG based on irregular R-R intervals. We hypothesize that a dominant frequency (DF) analysis of the ECG can differentiate between the two distinct arrhythmias, even when it is not evident by the presence of flutter waves or beat-to-beat regularity when looking at brief recordings. Methods: Canine model (n = 15, 10 controls and 5 Persistent AF animals with >6 months of AF) was used to test the hypothesis. Atrial arrhythmia was induced by rapid atrial pacing. Five blinded observers evaluated the 3 lead surface ECGs recorded during atrial arrhythmia and classified the rhythm as AFL/AT or AF. The 64-electrode Constellation (Boston Scientific) catheter was used to acquire left (entire group) and right (7 of 10 controls) atrial intracardiac electrograms. For the surface ECG and the intracardiac electrograms, Welch method with a hamming window and 50% overlap was used to calculate DF of two-minute segments. Mean of standard deviations of the DF values were calculated for both ECGs and intracardiac EGMs. Ground truth came from activations maps and DF analysis derived from the intracardiac electrograms recorded in the two chambers. Results: Rapid pacing induced atrial arrhythmias in all the control animals. The ECG in 8 of the 10 control cases was read as AF by at least 80% percent of observers even though the EGMs from the Constellation showed organized activation and consistent DF (STD of DF < 0.001) in all the electrodes confirming the arrhythmia as AFL in 10/10 cases. In the persistent AF group, the DF from the three lead ECGs were significantly different (Mean of STDs = 2.65 ± 0.99) whereas the DF in the control animals with AFL was consistent across all ECG channels (Mean of STDs < 0.001), and the DF in the control animals ECGs was in agreement with the DF of the intracardiac electrograms. Conclusion: Surface ECG recordings can mimic AF even when the underlying atrial arrhythmia is AFL in control canine models. DF variation of the signals from multiple surface ECG leads can help differentiate between the AF and AFL.

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Accurate ECG Diagnosis of Atrial Tachyarrhythmias Using Quantitative Analysis: A Prospective Diagnostic and Cost‐Effectiveness Study

Cited by 20 publications

References 45 publications

Electrocardiographic spatial loops indicate organization of atrial fibrillation minutes before ablation-related transitions to atrial tachycardia

Electrocardiographic spatial loops indicate organization of atrial fibrillation minutes before ablation-related transitions to atrial tachycardia

Atrial flutter and atrial tachycardia detection using Bayesian approach with high resolution time–frequency spectrum from ECG recordings

Atrial fibrillation observed on surface ECG can be atrial flutter or atrial tachycardia

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