Association of Atrial Fibrillation Episode Duration With Arrhythmia Recurrence Following Ablation

Andrade, Jason G.; Deyell, Marc W.; Macle, Laurent; Champagne, Jean; Leong‐Sit, Peter; Novak, Paul; Badra-Verdu, Mariano; Sapp, John L.; Khairy, Paul; Nattel, Stanley

doi:10.1001/jamanetworkopen.2020.8748

Cited by 40 publications

(38 citation statements)

References 20 publications

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“…Thus, regular checkups may allow for clinicians to manage arrhythmia progression in advance and improve AF treatment. Future work will focus on how different ablation sources may affect the different studied parameters [ 42 , 43 ], and will prospectively analyze how previous AF burden affects ablation outcome [ 3 ] with a larger cohort of patients.…”

Section: Discussionmentioning

confidence: 99%

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Characterization of Changes in P-Wave VCG Loops Following Pulmonary-Vein Isolation

Ortigosa

Cano

Sandberg

2021

Sensors

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Atrial fibrillation is the most common type of cardiac arrhythmia in clinical practice. Currently, catheter ablation for pulmonary-vein isolation is a well-established treatment for maintaining sinus rhythm when antiarrhythmic drugs do not succeed. Unfortunately, arrhythmia recurrence after catheter ablation remains common, with estimated rates of up to 45%. A better understanding of factors leading to atrial-fibrillation recurrence is needed. Hence, the aim of this study is to characterize changes in the atrial propagation pattern following pulmonary-vein isolation, and investigate the relation between such characteristics and atrial-fibrillation recurrence. Fifty patients with paroxysmal atrial fibrillation who had undergone catheter ablation were included in this study. Time-segment and vectorcardiogram-loop-morphology analyses were applied to characterize P waves extracted from 1 min long 12-lead electrocardiogram segments before and after the procedure, respectively. Results showed that P-wave vectorcardiogram loops were significantly less round and more planar, P waves and PR intervals were significantly shorter, and heart rate was significantly higher after the procedure. Differences were larger for patients who did not have arrhythmia recurrences at 2 years of follow-up; for these patients, the pre- and postprocedure P waves could be identified with 84% accuracy.

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Section: Discussionmentioning

confidence: 99%

“…Catheter ablation for pulmonary-vein isolation (PVI) is the recommended treatment to permanently restore the sinus rhythm when antiarrhythmic drugs fail [ 2 ]. Success rates for PVI are up to 80%, specially for patients with paroxysmal AF for whom recurrence rates are significantly lower after the procedure [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Changes in P-Wave VCG Loops Following Pulmonary-Vein Isolation

Ortigosa

Cano

Sandberg

2021

Sensors

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“…Hence, proper staging of AF and the start of effective treatment of AF is of utmost importance. Therefore, there is an urgent need to identify diagnostic biomarkers to stage AF and guide patient-tailored therapy [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Serum Heat Shock Protein Levels as Novel Biomarkers for Atrial Fibrillation

Marion

Lanters

Ramos

et al. 2020

Cells

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Background: Staging of atrial fibrillation (AF) is essential to understanding disease progression and the accompanied increase in therapy failure. Blood-based heat shock protein (HSP) levels may enable staging of AF and the identification of patients with higher risk for AF recurrence after treatment. Objective: This study evaluates the relationship between serum HSP levels, presence of AF, AF stage and AF recurrence following electrocardioversion (ECV) or pulmonary vein isolation (PVI). Methods: To determine HSP27, HSP70, cardiovascular (cv)HSP and HSP60 levels, serum samples were collected from control patients without AF and patients with paroxysmal atrial fibrillation (PAF), persistent (PeAF) and longstanding persistent (LSPeAF) AF, presenting for ECV or PVI, prior to intervention and at 3-, 6- and 12-months post-PVI. Results: The study population (n = 297) consisted of 98 control and 199 AF patients admitted for ECV (n = 98) or PVI (n = 101). HSP27, HSP70, cvHSP and HSP60 serum levels did not differ between patients without or with PAF, PeAF or LSPeAF. Additionally, baseline HSP levels did not correlate with AF recurrence after ECV or PVI. However, in AF patients with AF recurrence, HSP27 levels were significantly elevated post-PVI relative to baseline, compared to patients without recurrence. Conclusions: No association was observed between baseline HSP levels and the presence of AF, AF stage or AF recurrence. However, HSP27 levels were increased in serum samples of patients with AF recurrence within one year after PVI, suggesting that HSP27 levels may predict recurrence of AF after ablative therapy.

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“…Although this result was obtained using 12-lead ECG recordings instead of intracardiac measurements, this highlights the-yet not fully understood-underlying complexity of this arrhythmia. Despite great debate, the definition of types of AF is often subjective, and not necessarily based on EP characteristics [42]. For instance, AF is usually defined as paroxysmal, persistent, long-term persistent or permanent [1].…”

Section: B Persaf Aeg Classificationmentioning

confidence: 99%

Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation

Almeida

Soriano

Masè

et al. 2021

IEEE Trans. Biomed. Eng.

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Objective: Ablation treatment for persistent atrial fibrillation (persAF) remains challenging due to the absence of a 'ground truth' for atrial substrate characterization and the presence of multiple mechanisms driving the arrhythmia. We implemented an unsupervised classification to identify AEG clusters with similar patterns, which were then validated by AEGderived markers. Methods: 956 bipolar AEGs were collected from 11 persAF patients. CARTO variables (Biosense Webster; ICL, ACI and SCI) were used to create a 3D space, and subsequently used to perform an unsupervised classification with k-means. The characteristics of the identified groups were investigated using nine AEG-derived markers: sample entropy (SampEn), dominant frequency, organization index (OI), determinism, laminarity, recurrence rate (RR), peak-to-peak (PP) amplitude, cycle length (CL), and wave similarity (WS). Results: Five AEG classes with distinct characteristics were identified (F=582, P<0.0001). The presence of fractionation increased from class 1 to 5, as reflected by the nine markers. Class 1 (25%) included organized AEGs with high WS, determinism, laminarity, and RR, and low SampEn. Class 5 (20%) comprised fractionated AEGs with in low WS, OI, determinism, laminarity, and RR, and in high SampEn. Classes 2 (12%), 3 (13%) and 4 (30%) suggested different degrees of AEG organization. Conclusions: Our results expand and reinterpret the criteria used for automated AEG classification. The nine markers highlighted electrophysiological differences among the five classes found by the k-means, which could provide a more complete characterization of persAF substrate during ablation target identification in future clinical studies.  Index Terms-Atrial fibrillation; catheter ablation; electrophysiology mapping; unsupervised classification; k-means.

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Association of Atrial Fibrillation Episode Duration With Arrhythmia Recurrence Following Ablation

Cited by 40 publications

References 20 publications

Characterization of Changes in P-Wave VCG Loops Following Pulmonary-Vein Isolation

Characterization of Changes in P-Wave VCG Loops Following Pulmonary-Vein Isolation

Evaluating Serum Heat Shock Protein Levels as Novel Biomarkers for Atrial Fibrillation

Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation

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