Post-ablation Atrial Fibrillation Recurrence Research Articles

The Relationship Between Cardiac CT-based Left Atrial Structure and Epicardial Adipose Tissue and Postablation Atrial Fibrillation Recurrence Within 2 Years.

The aim of this study was to explore the association of cardiac CT-based left atrium (LA) structural and functional parameters and left atrial epicardial adipose tissue (LA-EAT) parameters with postablation atrial fibrillation (AF) recurrence within 2 years. Contrast-enhanced cardiac CT images of 286 consecutive AF patients (median age: 65 y; 97 females) who underwent initial ablation between June 2018 and June 2020 were retrospectively analyzed. Structural and functional parameters of LA, including maximum and minimum volume and ejection fraction of LA and left atrial appendage (LAA), and LA-EAT volume, were measured. The body surface area indexed maximum and minimum volume of LA (LAVImax, LAVImin) and LAA (LAAVImax, LAAVImin), and LA-EAT volume index (LA-EATVI) were calculated. Independent predictors of AF recurrence were determined using Cox regression analysis. The clinical predictors were added to the imaging predictors to build a combined model (clinical+imaging). The predictive performance of the clinical, imaging, and combined models was assessed using the area under the receiver operating characteristics curve (AUC). A total of 108 (37.8%) patients recurred AF within 2 years after ablation at a median follow-up of 24 months (IQR=11, 32). LA and LAA size and LA-EAT volume were significantly increased in patients with AF recurrence (P<0.05). After the multivariable regression analysis, LA-EATVI, LAAVImax, female sex, AF duration, and stroke history were independent predictors for AF recurrence. The combined model exhibited superior predictive performance compare to the clinical model (AUC=0.712 vs. 0.641, P=0.023) and the imaging model (AUC=0.712 vs. 0.663, P=0.018). Cardiac CT-based LA-EATVI and LAAVImax are independent predictors for postablation AF recurrence within 2 years and may provide a complementary value for AF recurrence risk assessment.

Does radiofrequency ablation procedural data improve the accuracy of identifying atrial fibrillation recurrence?

Radiofrequency ablation (RFA) using the CARTO 3D mapping system is a common approach for pulmonary vein isolation to treat atrial fibrillation (AF). Linkage between CARTO procedural data and patients' electronical health records (EHR) provides an opportunity to identify the ablation-related parameters that would predict AF recurrence. The objective of this study is to assess the incremental accuracy of RFA procedural data to predict post-ablation AF recurrence using machine learning model. Procedural data generated during RFA procedure were downloaded from CARTONET and linked to deidentified Mercy Health EHR data. Data were divided into train (70%) and test (30%) data for model development and validation. Automate machine learning (AutoML) was used to predict 1 year AF recurrence, defined as a composite of repeat ablation, electrical cardioversion, and AF hospitalization. At first, AutoML model only included Patients' demographic and clinical characteristics. Second, an AutoML model with procedural variables and demographical/clinical variables was developed. Area under receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI) were used to compare model performances using test data. Among 306 patients, 67 (21.9%) patients experienced 1-year AF recurrence. AUROC increased from 0.66 to 0.78 after adding procedural data in the AutoML model based on test data. For patients with AF recurrence, NRI was 32% for model with procedural data. Nine of 10 important predictive features were CARTO procedural data. From CARTO procedural data, patients with lower contact force in right inferior site, long ablation duration, and low number of left inferior and right roof lesions had a higher risk of AF recurrence. Patients with persistent AF were more likely to have AF recurrence. The machine learning model with procedural data better predicted 1-year AF recurrence than the model without procedural data. The model could be used for identification of patients with high risk of AF recurrence post ablation.

Risk and Protective Factors of Recurrence after Catheter Ablation for Atrial Fibrillation.

Atrial fibrillation (AF) is a common disease and is effectively managed through catheter ablation (CA). However, post-ablation AF recurrence can compromise patient outcomes, making the identification of associated risk factors crucially important. Factors influencing poor clinical outcomes include age, female sex, body mass index (BMI), non-paroxysmal AF, and comorbidities including diabetes mellitus (DM) and obstructive sleep apnea (OSA). Furthermore, the selected ablation strategy and employed technology are pivotal to long-term success in maintaining sinus rhythm control. The mechanisms of AF recurrence are complex and multifactorial; no single predictor is definitive. Thus, a personalized assessment of each patient should be tailored to the individual situation. A high risk of relapse does not preclude the option of ablation therapy, but rather underscores the necessity to address and manage underlying conditions contributing to AF pathogenesis, aiming to mitigate the risk of recurrence.

Abstract 16362: Does Extra-Pulmonary Triggers or Autonomic Neural Activity Affect the Rhythm Control by Anti-Arrhythmic Drugs in Patients With Post-Ablation Atrial Fibrillation Recurrence?

Introduction: Although the EAST-AFNET trial demonstrated the usefulness of atrial fibrillation (AF) rhythm control, including antiarrhythmic drugs (AADs), little is known about their effect on recurred AF after catheter ablation (CA). Hypothesis: We explored the effect of AADs depending on the presence of extra-pulmonary vein triggers (ExPVT) or post-ablation heart rate variability (HRV) in patients who recurred after AFCA. Methods: In this retrospective analysis of a single-center cohort, we analyzed 2,036 patients who underwent de-novo AFCA, and 486 of them had recurrent AF and subsequently underwent rhythm control with AADs. We investigated the effects of the extra-pulmonary vein (PV) triggers and post-procedural 3 rd month HRV (rMSSD; cut-off determined by Youden index) on the AAD responsiveness. Results: The post-AFCA recurrence was significantly higher in patients with ExPVT (Log-rank p&lt;0.001, HR 1.45 [1.16-1.83], p=0.001) or higher 3 rd month post procedure HRV-rMSSD (Log-rank p&lt;0.001, HR 1.36 [1.11-1.65], p=0.003) than their counterparts. Patients with ExPVT at de novo procedure had significantly higher 3 rd month rMSSD (15.0 [11.0-23.0] vs. 17.0 [11.0-28.0], p=0.022) and patients with high 3 rd month rMSSD showed a higher rate of ExPVT identified at the 2 nd repeat procedure (n=160, 41.0% vs. 22.2%, p=0.019). Among those patients how recurred AF after AFCA, post-AAD recurrence did not differ depending on ExPVT (Log-rank p=0.455, HR 1.12 [0.78-1.69], p=0.436) or rMSSD (Log-rank p=0.457, HR 1.16 [0.87-1.55], p=0.300). Post-AAD recurrence did not differ between class IC and III AADs (p for interaction = 0.311). Conclusion: ExPVT and post-procedural high rMSSD are independent risk factors for post-AFCA recurrences but not for AAD response in recurred AF patients. Whether AADs may suppress ExPVT and modulate cardiac autonomic activity after post-AFCA recurrences need further investigation.

Epicardial Adipose Tissue and Atrial Fibrillation Recurrence following Catheter Ablation: A Systematic Review and Meta-Analysis.

(1)Introduction: Catheter ablation has become a cornerstone for the management of patients with atrial fibrillation (AF). Nevertheless, recurrence rates remain high. Epicardial adipose tissue (EAT) has been associated with AF pathogenesis and maintenance. However, the literature has provided equivocal results regarding the relationship between EAT and post-ablation recurrence.(2) Purpose: to investigate the relationship between total and peri-left atrium (peri-LA) EAT with post-ablation AF recurrence. (3) Methods: major electronic databases were searched for articles assessing the relationship between EAT, quantified using computed tomography, and the recurrence of AF following catheter ablation procedures. (4) Results: Twelve studies (2179 patients) assessed total EAT and another twelve (2879 patients) peri-LA EAT. Almost 60% of the included patients had paroxysmal AF and recurrence was documented in 34%. Those who maintained sinus rhythm had a significantly lower volume of peri-LA EAT (SMD: -0.37, 95%; CI: -0.58-0.16, I2: 68%). On the contrary, no significant difference was documented for total EAT (SMD: -0.32, 95%; CI: -0.65-0.01; I2: 92%). No differences were revealed between radiofrequency and cryoenergy pulmonary venous isolation. No publication bias was identified. (5) Conclusions: Only peri-LA EAT seems to be predictive of post-ablation AF recurrence. These findings may reflect different pathophysiological roles of EAT depending on its location. Whether peri-LA EAT can be used as a predictor and target to prevent recurrence is a matter of further research.

The Impact of Regional Maximum Tolerated Interlesion Distance on the Long-Term Ablation Outcomes in Ablation Index Guided Pulmonary Vein Isolation for Atrial Fibrillation.

An adequate interlesion distance (ILD) applied during point-by-point pulmonary vein (PV) isolation for atrial fibrillation (AF) has never been established. We hypothesized that maximum tolerated ILD may differ between PV regions and may influence long-term ablation outcomes. A total of 260 AF patients underwent PV isolation with 3D electroanatomical platform. Postablation, ILD values were classified into 5 groups (6-5.5 mm, 5.5-5.0 mm, 5.0-4.5 mm, 4.5-4.0 mm and <4.0 mm); the number of tags in each group was calculated and correlated with postablation AF recurrence (AFR). All measurements were performed globally for the entire encirclement around each individual PV and regionally for designated PV anatomic segments. Single-procedure freedom from AF was 81% for paroxysmal and 66% for persistent AF at 12 months. Global analysis showed that AFR was not related to median ILD nor the number of lesions within each ILD tag group for any PV. Segmental analysis showed that AFR was not related to median ILD. However, the presence of tags from the 5.5-6.0 mm ILD group located on the posterior aspect of right upper PV (RUPV) correlated with AFR. This was confirmed in a multivariable logistic regression model. Maximum tolerated ILD of 6.0 mm translated into well-accepted ablation results. However, the study suggests that it may be inadequate at the posterior aspect of RUPV.

Atrial Periodic Source Spectrum from Preoperative Body Surface Potentials Predicts Long-term Recurrence of Atrial Fibrillation.

About half of patients experience recurrence of atrial fibrillation (AF) within three to five years after a single catheter ablation procedure. The suboptimality of the long-term outcomes likely results from the inter-patient variability of AF mechanisms, which can be remedied by improved patient screening. We aim to improve the interpretation of body surface potentials (BSPs), such as 12-lead electrocardiograms and 252-lead BSP maps, to aid preoperative patient screening. We developed the Atrial Periodic Source Spectrum (APSS), a novel patient-specific representation based on atrial periodic content, computed on the f-wave segments of patient BSPs, using a second-order blind source separation and a Gaussian Process for regression. With follow-up data, Cox's proportional hazard model was used to select the most relevant feature from preoperative APSSs responsible for AF recurrence. Over 138 persistent AF patients, the presence of highly periodic content with cycle lengths between 220-230 ms or 350-400 ms indicates higher risks of 4-year post-ablation AF recurrence (log-rank test, p-value ). Preoperative BSPs demonstrate effective prediction in the long-term outcomes, highlighting their potential for patient screening in AF ablation therapy.

RENIN-ANGIOTENSIN-ALDOSTERONE BLOCKADE AND ITS PREDICTION OF LATE RECURENCE OF ATRIAL FIBRILLATION AFTER RADIOFREQUENCY ABLATION

Objective: Hypertension is one of the main triggers of atrial fibrillation. Patients with hypertension have 1.7 times higher risk of developing atrial fibrillation. Opinions differ on the use of RAAS blockers in atrial fibrillation. The aim is to evaluate the effect of RAAS blockers in the prevention of atrial fibrillation on the post-ablation prognosis of the patient. Design and method: A retrospective analysis of 221 patients who underwent radiofrequency ablation of atrial fibrillation at the First Department of Internal Medicine - Cardioangiology of St. Anne's University Hospital in Brno from 1 January to 31 December 2019 was performed. Recurrence within the first three months was designated as early, and in the following months as late. Results: The median age of the study population (N = 221) was 63 years, with 67.4% of men. According to pre-ablation transesophageal echocardiography, the mean left atrial dimension was 45.3mm and left ventricular ejection fraction was 59.8%. Among the comorbidities, hypertension (63.3%) and dyslipidaemia (41.6%) were the most common, followed by diabetes mellitus (14.0%), ischemic heart disease (7.2%), history of stroke (6.3%), chronic obstructive pulmonary disease (5.0%). 33.0% had a history of nicotinism. Among the baseline antihypertensive groups, beta-blockers were the most represented (69.2%) followed by angiotensin-converting enzyme inhibitors (37.5), angiotensin-receptor blockers (20.4%), calcium channel blockers (32.1%) and diuretics (32.1%). There was not a significant difference in the representation of each group of antihypertensives between the populations. n the group of patients treated with ACEis/ARBs (57.9%), the mean blood pressure resulting from pre- and post-ablation measurements was the same 149/81mm Hg. No significant differences in left atrial size or capture of early or late postablation recurrence (HR 1.26, 95% CI 0.84-1.90, p = 0.265) were detected in the RAAS inhibitor group relative to patients without ACEis/ARBs in therapy. Conclusions: Conventionally administered ACEis/ARBs before ablation procedure did not lead to a reduction in the detection of late postablation recurrence of atrial fibrillation. Despite the documented benefit of RAAS blocker therapy in atrial fibrillation patients, their routine administration before ablation procedure aimed at improving postablation prognosis was not evaluated as justified.

PO-04-208 CLINICAL APPLICATION OF ARTIFICIAL INTELLIGENCE IN PREDICTION OF RECURRENCE IN ATRIAL FIBRILLATION PATIENTS WITH CATHETER ABLATION

The atrial fibrillation (AF) recurrence is still a challenging issue after catheter ablation. It is important to identify which patients are intended to have a post-ablation recurrence before ablation for decision-making. We aimed to build AI models in PVCT images and clinical variables. We also combined deep learning in PVCT images and machine learning of clinical parameters by nonparametric statistical method or I-score to build an ensemble model to predict the post-ablation one-year AF recurrence. We retrospectively analyzed 518 PAF patients who have undergone catheter ablation of PAF (Table 1). PVCT geometric slices (2-3mm for each slice, 20-200 slices for each patient, a total of 36943 images of slices in 518 AF patients) were used in the deep learning process for the prediction of AF trigger origin as model 1. In 1 year follow-up, there was no AF recurrence in 388 (74.9%) patients (Group 1) and AF recurrence in 130 (25.1%) patients (Group 2). The deep learning process (EfficientNet) of cardiac CT geometric slices was applied for the prediction of AF recurrence. A total of 43 clinical variables were obtained before catheter ablation, including baseline characteristics, personal habits, medical histories, a stroke risk score of AF, laboratory values of blood tests, transthoracic echocardiographic parameters, left atrial volume calculated by 3D geometric reconstruction, and medications. Using different machine learning methods, the predictive performance of clinical variables using all variables or selected features by Nonparametric Statistics ranged from an AUC of 0.691 to 0.760. the predictive performance of clinical variables by I-Score was between AUC of 0.702 to 0.729 (Table 2). The best predictive performance was an AUC of 0.729 using I-Score rank 3 parameters (Table 3) and the CatBoost machine learning method. We combined the features of PVCT images and clinical variables. The ensemble model was able to promote the predictive performance up to an AUC of 0.722 (accuracy of 75.9%, sensitivity of 50.0%, and specificity of 83.7%) in the test set. Deep-learning AI using pre-ablation cardiac CT and clinical variables can be applied in the prediction of recurrence in AF patients receiving catheter ablation. Application of this model may identify patients with post-ablation AF recurrence.

PO-03-092 MACHINE LEARNING ANALYSIS OF THE PREDICTORS OF AF RECURRENCE POST-ABLATION IN PATIENTS UNDERGOING PRE-ABLATION MRI

Catheter ablation, a widely performed rhythm control strategy for atrial fibrillation (AF), has variable results in the complete suppression of arrhythmia recurrence, especially in obese patients. Structural remodeling of the left atrium (LA), evidenced by LA enlargement and fibrosis, is a well-known substrate for AF. Epicardial adipose tissue (EAT) is thought to be a crucial factor mediating cardiovascular disease in obesity, it can result in electrical heterogeneity and local conduction block forming a substrate for AF. We aimed to apply a machine learning approach to assess the predictors of AF recurrence following catheter ablation in AF patients undergoing pre-ablation cardiac magnetic resonance (CMR). 101 AF patients underwent CMR prior to catheter ablation. Fibrotic remodeling was assessed using the late gadolinium enhancement sequence. EAT was assessed using the novel fat-water separation 3D Dixon sequence. Panel A shows posterior and anterior views of a representative LA model showing fibrotic remodeling and EAT. Patients were followed for AF recurrence using ambulatory monitoring and 12-lead ECGs. A random forest classifier with 5x stratified cross-validation was trained to predict AF recurrence post-ablation and SHapley Additive exPlanations (SHAP) analysis was used to assess feature importance in the prediction of AF recurrence. During an average follow-up period of 1 year, post-ablation AF recurrence occurred in 31 (30.7%) patients. Patients with AF recurrence post-ablation had higher LA EAT index (20.7 [16.9, 30.4] vs 13.7 [10.5, 20.1] mL/m2, p<0.001), and higher LA volume index (66 [52.6, 77.5] vs 49.9 [37.7, 61.8] mL/m2, p=0.001). There was a trend toward a higher fibrosis burden in patients who had an AF recurrence (18.6% vs 16.1%, p=0.076). The classifier predicted AF recurrence post-ablation with an AUC of 0.67 ± 0.09 (Panel B). SHAP analysis revealed that for the overall population, the three most important features in the prediction of AF recurrence post-ablation were LA volume index, LA EAT index, and LA fibrosis (Panel C). LA enlargement, fibrosis and EAT, markers with clear ties to AF pathophysiology, are predictors of AF recurrence after ablation. Future studies testing the value of an imaging-based ablation failure prediction calculator, as well as studies to elucidate the mechanism of ablation failure, are required.

Registry for Evaluating Healthy Life Expectancy and Long-Term Outcomes after Catheter Ablation of Atrial Fibrillation in the Very Elderly (REHEALTH AF) study: rationale and design of a prospective, multicentre, observational, comparative study

IntroductionData are lacking on the extent to which patients with non-valvular atrial fibrillation (AF) who are aged ≥80 years benefit from ablation treatment. The question pertains especially to patients’ postablation...

MRI-quantified left atrial epicardial adipose tissue predicts atrial fibrillation recurrence following catheter ablation.

Epicardial adipose tissue (EAT) plays a significant role in promoting atrial fibrillation (AF) due to its proinflammatory properties and anatomic proximity to the myocardium. We sought to assess whether left atrial (LA) EAT volume is associated with AF recurrence following catheter ablation. EAT was assessed via the 3D MRI Dixon sequence in 101 patients undergoing AF ablation. Patients were followed for arrhythmia recurrence. During an average follow-up period of 1 year, post-ablation AF recurrence occurred in 31 (30.7%) patients. LA EAT index was higher in those with compared to without recurrence (20.7 [16.9, 30.4] vs. 13.7 [10.5, 20.1] mL/m2, p < 0.001), and so was LA volume index (66 [52.6, 77.5] vs. 49.9 [37.7, 61.8] mL/m2, p = 0.001). Cox regression analysis showed LA EAT (HR = 1.089; 95% CI: [1.049-1.131], p < 0.001) to be an independent predictor of post-ablation AF recurrence. The ROC curve for LA EAT index in the prediction of AF recurrence had an AUC of 0.77 (95% CI 0.68-0.86, p < 0.001) and showed an optimal cutoff value of 14.29 mL/m2 to identify patients at risk of post-ablation AF recurrence. Integrating LA EAT with clinical risk factors improved prediction of AF recurrence (AUC increased from 0.65 to 0.79, DeLong test p = 0.044). Kaplan-Meier analysis for recurrence-free survival showed a significant difference between two groups of patients identified by the optimal LA EAT index cutoff of 14.29 mL/m2 (log rank = 14.79; p < 0.001). EAT quantified using cardiac MRI, a reproducible and widely accessible imaging parameter, is a strong and independent predictor of post-ablation AF recurrence.

Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation

Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03–3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment.Graphical

Abstract 14749: Assessment for Neurocognitive Change After Catheter Ablation for Atrial Fibrillation

Introduction: Several studies have been conducted to evaluate the neurocognitive effects of catheter ablation for atrial fibrillation. However, these studies have found mixed results. Theoretically, silent peri-procedural stroke might yield a worsening of neurocognitive function, though normalization of heart rhythms might yield improvement. The purpose of this study was to prospectively follow patients after catheter-ablation for paroxysmal or persistent atrial fibrillation with serial telephone-based Montreal Cognitive Assessments (t-MoCA) over 6 months to evaluate for changes in neurocognitive function. Hypothesis: No change in t-MoCA scores between baseline and 1-month, 3-months, and 6-months after catheter ablation for atrial fibrillation. Methods: All consenting patients who underwent first time or redo catheter ablation for atrial fibrillation (with either radiofrequency- or cryo-ablation) between January 2021 and May 2022 were enrolled in the study. A t-MoCA was conducted to measure cognitive function at baseline, 1 month, 3 months, and 6 months from the date of catheter ablation. Only patients who completed at least 1 month of follow-up were included for analysis. Paired t-tests and one-way ANOVA were used to assess for significant differences in t-MoCA scores. Results: 42 patients met criteria for analysis. Paired two-tailed t-test values at 1-month, 3-months, and 6-months demonstrated an increase in t-MoCA score by 2.17 (n=42, p = 0.036), 3.08 (n=27, p = 0.005), and 3.06 (n=24, p = 0.006) respectively when compared to baseline. One-way ANOVA testing showed no significant differences between the 1-month, 3-month, and 6-month scores (p = 0.73). Conclusions: Patients undergoing first time or redo catheter ablation for atrial fibrillation had significant improvement in t-MoCA scores at 1-month, 3-months, and 6-months post-ablation. The improvement seen at 1-month was sustained throughout the 6-months of follow-up. Further long-term assessment is needed to determine if this effect persists over a longer period of time and to potentially correlate these findings with post-ablation atrial fibrillation recurrence.

Machine learning applications in cardiac computed tomography: a composite systematic review.

Artificial intelligence and machine learning (ML) models are rapidly being applied to the analysis of cardiac computed tomography (CT). We sought to provide an overview of the contemporary advances brought about by the combination of ML and cardiac CT. Six searches were performed in Medline, Embase, and the Cochrane Library up to November 2021 for (i) CT-fractional flow reserve (CT-FFR), (ii) atrial fibrillation (AF), (iii) aortic stenosis, (iv) plaque characterization, (v) fat quantification, and (vi) coronary artery calcium score. We included 57 studies pertaining to the aforementioned topics. Non-invasive CT-FFR can accurately be estimated using ML algorithms and has the potential to reduce the requirement for invasive angiography. Coronary artery calcification and non-calcified coronary lesions can now be automatically and accurately calculated. Epicardial adipose tissue can also be automatically, accurately, and rapidly quantified. Effective ML algorithms have been developed to streamline and optimize the safety of aortic annular measurements to facilitate pre-transcatheter aortic valve replacement valve selection. Within electrophysiology, the left atrium (LA) can be segmented and resultant LA volumes have contributed to accurate predictions of post-ablation recurrence of AF. In this review, we discuss the latest studies and evolving techniques of ML and cardiac CT.

Recurrence of atrial fibrillation postablation: which is the most effective approach for detection?

Over the last 20 years, catheter ablation of atrial fibrillation (AF) has evolved from a research tool into a fundamental therapeutic measure, with the potential to improve symptoms, quality of life, and even risk of major adverse cardiac events (among patients with heart failure and a reduced ejection fraction). Notwithstanding the tremendous evolution in techniques and tools, risk of AF recurrences postablation is not negligible, and a comprehensive structured follow-up is highly needed to deliver optimal patient care. In this follow-up process, monitoring of heart rhythm is quintessential to detect recurrences, and may be accomplished by means of symptoms-triggered, intermittent, or continuous monitors. In recent years, the development and widespread adoption of implantable cardiac monitors, by allowing continuous long-term rhythm assessment, has surged to become the gold-standard strategy, both in research settings and in clinical practice. In this review, we both summarize the present state-of-the art on the detection of postablation AF recurrences and provide future perspectives on this emerging yet often neglected topic, aiming to give practical hints for evidence-based, personalized patient care.

New Radiomic Markers of Pulmonary Vein Morphology Associated With Post-Ablation Recurrence of Atrial Fibrillation.

Objective: To identify radiomic and clinical features associated with post-ablation recurrence of AF, given that cardiac morphologic changes are associated with persistent atrial fibrillation (AF), and initiating triggers of AF often arise from the pulmonary veins which are targeted in ablation. Methods: Subjects with pre-ablation contrast CT scans prior to first-time catheter ablation for AF between 2014–2016 were retrospectively identified. A training dataset (D1) was constructed from left atrial and pulmonary vein morphometric features extracted from equal numbers of consecutively included subjects with and without AF recurrence determined at 1 year. The top-performing combination of feature selection and classifier methods based on C-statistic was evaluated on a validation dataset (D2), composed of subjects retrospectively identified between 2005–2010. Clinical models (n}{}text{M}_{mathrm {C}}n) were similarly evaluated and compared to radiomic (n}{}text{M}_{mathrm {R}}n) and radiomic-clinical models (n}{}text{M}_{mathrm {RC}}n), each independently validated on D2. Results: Of 150 subjects in D1, 108 received radiofrequency ablation and 42 received cryoballoon. Radiomic features of recurrence included greater right carina angle, reduced anterior-posterior atrial diameter, greater atrial volume normalized to height, and steeper right inferior pulmonary vein angle. Clinical features predicting recurrence included older age, greater BMI, hypertension, and warfarin use; apixaban use was associated with reduced recurrence. AF recurrence was predicted with radio-frequency ablation models on D2 subjects with C-statistics of 0.68, 0.63, and 0.70 for radiomic, clinical, and combined feature models, though these were not prognostic in patients treated with cryoballoon. Conclusions: Pulmonary vein morphology associated with increased likelihood of AF recurrence within 1 year of catheter ablation was identified on cardiac CT. Significance: Radiomic and clinical features-based predictive models may assist in identifying atrial fibrillation ablation candidates with greatest likelihood of successful outcome.

Abstract 10366: Comparative Evaluations of Six Risk Scores Proposed for Baseline Prediction of Atrial Fibrillation Recurrence Post Catheter Ablation

Background: Being able to identify patients who are at risk of arrhythmia recurrence following catheter ablation is important for prognostication, shared-decision making, etc. While numerous predictive models for atrial fibrillation recurrence (AFR) have been proposed, few models have underwent external validation, and few studies compared multiple models using the same patient cohort. Aims: To evaluate six prediction models using an external dataset. Methods: Data from 632 patients was pooled from two independent clinical trials that enrolled patients with anti-arrhythmic drug refractory atrial fibrillation who underwent catheter ablation. Primary outcome for both trials was documented atrial tachyarrhythmia (atrial fibrillation/flutter/tachycardia as adjudicated by a clinical committee blinded to treatment strategy). We compared 6 models for predicting AFR recorded between days 91-365 post ablation using standard metrics and ranked them according to the positive and negative clinical utility indices. Results: As the figure shows, the top performing model was CHA2DS2-VASc, followed by DR-FLASH, albeit both achieved positive and negative predictive values lower than 65%. Many models achieved high specificity but low sensitivity, except for CAAP-AF, which achieved high sensitivity but low specificity. In summary, all achieved area under receiver operating characteristic curve lower than 56% and were deemed to have poor clinical utility (less than 0.5 out of 1) when evaluated on our dataset. Conclusion: All models performed poorly and had objectively limited clinical utility. There remains a need to develop generalizable tools for predicting post ablation AFR.

Comparison of the predictive value of ten risk scores for outcomes of atrial fibrillation patients undergoing radiofrequency pulmonary vein isolation

BackgroundA significant number of patients experience recurrent atrial fibrillation (AF) after ablation. Various risk scores have been described that may predict outcomes after AF ablation. In this study, we aimed to compare ten previously described risk scores with regard to their predictive value for post-ablation AF recurrence and procedural complications. MethodsA total of 482 AF patients (63% paroxysmal AF, 66% male, mean age 62 ± 9 years) undergoing initial radiofrequency pulmonary vein isolation (PVI) were included in the present analysis. Prior to ablation, all patients underwent both transthoracic echocardiography (TTE) and either cardiac CT imaging or CMR imaging. The following risk scores were calculated for each patient: APPLE, ATLAS, BASE-AF2, CAAP-AF, CHADS2, CHA2DS2-VASc, DR-FLASH, HATCH, LAGO and MB-LATER. ResultsMedian follow-up was 16 (12–31) months. AF recurrence after a 90-day blanking period was observed in 199 patients (41%), occurring after a median of 183 (124–360) days. AF recurrence was less frequent in paroxysmal AF patients compared to non-paroxysmal AF patients (34% vs. 54%, p < 0.001). Overall periprocedural complication rate was 6%. All scores, except the HATCH score, demonstrated statistically significant but poor predictive value for recurrent AF after ablation (area under curve [AUC] 0.553–0.669). CHA2DS2-VASc and CAAP-AF were the only risk scores with predictive value for procedural complications (AUC 0.616, p = 0.043; AUC 0.615, p = 0.044; respectively). ConclusionsCurrently available risk scores perform poorly in predicting outcomes after AF ablation. These data suggest that the utility of these scores for clinical decision-making is limited.

Is Epicardial Adipose Tissue Associated with Atrial Fibrillation Following Cardiac Surgery? A Systematic Review and Meta-Analysis.

Although epicardial adipose tissue (EAT) has been proven to be related to atrial fibrillation (AF) and post-ablation AF recurrence, the association between EAT and AF after cardiac surgery (AFACS) remains unclear. This study was a systematic review and meta-analysis that assessed the relationship between EAT and AFACS. Electronic databases were systematically searched for "atrial fibrillation" and "epicardial adipose tissue." The analysis was stratified according to the EAT measurement into three meta-analyses as (1) total EAT volume, (2) left atrial (LA)-EAT volume, and (3) EAT thickness. Standardized mean difference (SMD) was estimated using a random effects model. Eight articles with 10 studies (546 patients) were included. The meta-analysis revealed that EAT was higher in those with AFACS irrespective of the EAT measurement (total EAT volume: SMD = 0.56 mL, 95% confidence interval, CI = 0.56-1.10 mL, I2 = 0.90, P = .04; EAT thickness: SMD = 0.85 mm, 95% CI = 0.04-1.65 mm, I2 = 0.90, P = .04; LA-EAT volume: SMD = 0.57 mL, 95% CI = 0.23-0.92 mL, I2 = 0.00, P = .001). EAT was higher in patients with AFACS, measured either as volume or thickness.