Predicting recurrent atrial fibrillation after catheter ablation: a systematic review of prognostic models

Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques

BACKGROUND

Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machine learning model to forecast the early recurrence of atrial fibrillation following catheter ablation.

METHODS

A prospective longitudinal study was conducted using data from the Iranian AF registry. The dataset included 402 consecutive AF patients who underwent radiofrequency catheter ablation. The primary outcome was early recurrence of AF within 3 months' post-ablation. Data preprocessing and feature selection were performed, followed by the development and evaluation of various machine learning models. The CatBoost model was selected as the best-performing model.

RESULTS

The study population had a mean age of 57.30 ± 14.05 years, and 61.4% were male. AF recurrence occurred in 26.1% of patients. The CatBoost model, utilizing 35 features, achieved an accuracy of 92.5% in predicting AF recurrence. The model demonstrated high sensitivity (88.6%) and specificity (94.0%), with an area under the ROC curve of 0.96. Paroxysmal AF, BUN, Cr, age, mitral regurgitation, LA velocity, and mild valvular heart disease were among the most important predictive features.

CONCLUSION

Machine learning methods, particularly the CatBoost model, demonstrate high accuracy in predicting early catheter ablation outcomes in AF patients. The developed model has the potential to improve patient care and decision-making by identifying patients most likely to benefit from the procedure. Further studies with larger sample sizes and external validation are warranted to assess the generalizability of this method for catheter ablation outcome prediction in AF patients.

Biomarker-based prediction of sinus rhythm in atrial fibrillation patients: the EAST-AFNET 4 biomolecule study

BACKGROUND AND AIMS

In patients with atrial fibrillation (AF), recurrent AF and sinus rhythm during follow-up are determined by interactions between cardiovascular disease processes and rhythm control therapy. Predictors of attaining sinus rhythm at follow-up are not well known.

METHODS

To quantify the interaction between cardiovascular disease processes and rhythm outcomes, 14 biomarkers reflecting AF-related cardiovascular disease processes in 1586 patients in the EAST-AFNET 4 biomolecule study (71 years old, 45% women) were quantified at baseline. Mixed logistic regression models including clinical features were constructed for each biomarker. Biomarkers were interrogated for interaction with early rhythm control. Outcome was sinus rhythm at 12 months. Results were validated at 24 months and in external datasets.

RESULTS

Higher baseline concentrations of three biomarkers were independently associated with a lower chance of sinus rhythm at 12 months: angiopoietin 2 (ANGPT2) (odds ratio [OR] .76 [95% confidence interval .65-.89], P < .001), bone morphogenetic protein 10 (BMP10) (OR .83 [.71-.97], P = .017), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) (OR .73 [.60-.88], P < .001). Analysis of rhythm at 24 months confirmed the results. Early rhythm control interacted with the predictive potential of NT-proBNP (Pinteraction = .033). The predictive effect of NT-proBNP was reduced in patients randomized to early rhythm control (usual care: OR .64 [.51-.80], P < .001; early rhythm control: OR .90 [.69-1.18], P = .453). External validation confirmed that low concentrations of ANGPT2, BMP10, and NT-proBNP predict sinus rhythm during follow-up.

CONCLUSIONS

Low concentrations of ANGPT2, BMP10, and NT-proBNP identify patients with AF who are likely to attain sinus rhythm during follow-up. The predictive ability of NT-proBNP is attenuated in patients receiving rhythm control.

2024 European Heart Rhythm Association/Heart Rhythm Society/Asia Pacific Heart Rhythm Society/Latin American Heart Rhythm Society expert consensus statement on catheter and surgical ablation of atrial fibrillation

In the last three decades, ablation of atrial fibrillation (AF) has become an evidence-based safe and efficacious treatment for managing the most common cardiac arrhythmia. In 2007, the first joint expert consensus document was issued, guiding healthcare professionals involved in catheter or surgical AF ablation. Mounting research evidence and technological advances have resulted in a rapidly changing landscape in the field of catheter and surgical AF ablation, thus stressing the need for regularly updated versions of this partnership which were issued in 2012 and 2017. Seven years after the last consensus, an updated document was considered necessary to define a contemporary framework for selection and management of patients considered for or undergoing catheter or surgical AF ablation. This consensus is a joint effort from collaborating cardiac electrophysiology societies, namely the European Heart Rhythm Association, the Heart Rhythm Society, the Asia Pacific Heart Rhythm Society, and the Latin American Heart Rhythm Society.

Radiofrequency balloon ablation: 1-year outcomes of the AURORA study

BACKGROUND

A novel irrigated radiofrequency balloon (RFB) for pulmonary vein isolation (PVI) integrated into a 3D mapping platform was recently launched.

METHODS

Patients undergoing a first atrial fibrillation (AF) ablation at two German high-volume EP centers were included into the prospective AURORA registry. All patients underwent clinical follow-up (FU) at 90, 180, and 360 days following ablation including 48-h Holter ECGs.

RESULTS

A total of 99 patients were enrolled (43/99 (43.4%) women, median age 67 years (interquartile range [IQR] 59-74), 43/99 (43.4%) persistent AF (Pers-AF), median left ventricular ejection fraction (LVEF) 60% (IQR 62-55)). Eighty-eight patients completed the follow-up. Acute PVI was achieved in 383/383 (100%) PV. Single-shot PVI was achieved in 211/383 (55.1%) PVs. Primary adverse events occurred in 3% of patients (1 postprocedural pharyngeal bleeding, 1 myocardial infarction, 1 non-cardiovascular death); no pericardial effusion, stroke, or phrenic nerve paralysis was observed. Median ablation and procedure times were 23 (IQR 18-32) and 67 (IQR 57-85) min, respectively. Median dose area product was 761 (IQR 509-1534) mGycm2. AF-free survival after a median FU of 361 (IQR 261-375) days was 78.4% for paroxysmal AF (PAF) and 75.4% for Pers-AF (p value = 0.828). Early recurrence of atrial tachyarrhythmia at the 90-day visit was the only independent predictor for AF recurrence at 1 year upon multiple regression analysis (hazard ratio [HR] 3.198; 95% confidence interval [95% CI] 1.036-10.32, p value = 0.0433).

CONCLUSION

RFB-based PVI is acutely successful, appears safe, and has comparable rhythm outcomes to other single-shot AF ablation tools. A recurrence of AF at 90 days predicts later AF recurrence.

Atrial Fibrillation in Patients with Very High Risk for Stroke and Adverse Events-Insights from the Observational ARENA Study

Background: Atrial fibrillation (AF) is a major cause of stroke. An individual risk estimation remains challenging, as AF patients with and without cerebrovascular event (CVE) may differ in yet unknown factors beyond those covered by the CHA2DS2-VASc score. We aimed to identify differences between AF patients with and without CVE with regard to AF characteristics and treatment, vascular risk factors and comorbidities, prognosis and outcome. Methods: We analyzed patients included in the Atrial Fibrillation Rhine-Neckar Region (ARENA) Project, an observational cohort study of patients with AF. Patients were recruited by their general practitioner or during a hospital stay and were divided into two groups for the present analysis: patients with acute CVE at baseline and/or history of CVE versus patients without CVE. Follow-up at 1 year was conducted via phone call. Results: Of 2061 included patients (60.6% male), 292 (14.2%) belonged to the CVE group. Patients in the CVE group were older (mean age 74.6 versus 71.7 years; p < 0.001) and had a higher CHA2DS2-VASc score at baseline (5.3 versus 3.3 points; p < 0.001) based on the preceding CVE. Moreover, patients with either acute or chronic CVE had a larger left atrium (median diameter 47/46 mm versus 44 mm; p = 0.001). Patients with acute CVE had structural heart diseases (p < 0.001) less frequently than patients with previous or without CVE. Mortality at 1 year (HR 1.95; 95%-CI 1.37-2.78) was more frequent in the CVE group (p < 0.001). During 1-year of follow-up, stroke occurred more frequently in survivors with CVE (2.9% versus 0%; p < 0.001). Conclusions: AF patients with CVE have a significantly worse prognosis than AF patients without CVE. Atrial structural remodeling, underlying cardiovascular disease, stroke-induced heart injury and further unidentified factors may account for this finding. Characterization of AF patients including echocardiography to detect atrial structural remodeling may be helpful in risk stratification beyond classical scores.

Immune response caused by M1 macrophages elicits atrial fibrillation-like phenotypes in coculture model with isogenic hiPSC-derived cardiomyocytes

BACKGROUND

Atrial fibrillation has an estimated prevalence of 1.5-2%, making it the most common cardiac arrhythmia. The processes that cause and sustain the disease are still not completely understood. An association between atrial fibrillation and systemic, as well as local, inflammatory processes has been reported. However, the exact mechanisms underlying this association have not been established. While it is understood that inflammatory macrophages can influence cardiac electrophysiology, a direct, causative relationship to atrial fibrillation has not been described. This study investigated the pro-arrhythmic effects of activated M1 macrophages on human induced pluripotent stem cell (hiPSC)-derived atrial cardiomyocytes, to propose a mechanistic link between inflammation and atrial fibrillation.

METHODS

Two hiPSC lines from healthy individuals were differentiated to atrial cardiomyocytes and M1 macrophages and integrated in an isogenic, pacing-free, atrial fibrillation-like coculture model. Electrophysiology characteristics of cocultures were analysed for beat rate irregularity, electrogram amplitude and conduction velocity using multi electrode arrays. Cocultures were additionally treated using glucocorticoids to suppress M1 inflammation. Bulk RNA sequencing was performed on coculture-isolated atrial cardiomyocytes and compared to meta-analyses of atrial fibrillation patient transcriptomes.

RESULTS

Multi electrode array recordings revealed M1 to cause irregular beating and reduced electrogram amplitude. Conduction analysis further showed significantly lowered conduction homogeneity in M1 cocultures. Transcriptome sequencing revealed reduced expression of key cardiac genes such as SCN5A, KCNA5, ATP1A1, and GJA5 in the atrial cardiomyocytes. Meta-analysis of atrial fibrillation patient transcriptomes showed high correlation to the in vitro model. Treatment of the coculture with glucocorticoids showed reversal of phenotypes, including reduced beat irregularity, improved conduction, and reversed RNA expression profiles.

CONCLUSIONS

This study establishes a causal relationship between M1 activation and the development of subsequent atrial arrhythmia, documented as irregularity in spontaneous electrical activation in atrial cardiomyocytes cocultured with activated macrophages. Further, beat rate irregularity could be alleviated using glucocorticoids. Overall, these results point at macrophage-mediated inflammation as a potential AF induction mechanism and offer new targets for therapeutic development. The findings strongly support the relevance of the proposed hiPSC-derived coculture model and present it as a first of its kind disease model.

2024 European Heart Rhythm Association/Heart Rhythm Society/Asia Pacific Heart Rhythm Society/Latin American Heart Rhythm Society expert consensus statement on catheter and surgical ablation of atrial fibrillation

In the last three decades, ablation of atrial fibrillation (AF) has become an evidence-based safe and efficacious treatment for managing the most common cardiac arrhythmia. In 2007, the first joint expert consensus document was issued, guiding healthcare professionals involved in catheter or surgical AF ablation. Mounting research evidence and technological advances have resulted in a rapidly changing landscape in the field of catheter and surgical AF ablation, thus stressing the need for regularly updated versions of this partnership which were issued in 2012 and 2017. Seven years after the last consensus, an updated document was considered necessary to define a contemporary framework for selection and management of patients considered for or undergoing catheter or surgical AF ablation. This consensus is a joint effort from collaborating cardiac electrophysiology societies, namely the European Heart Rhythm Association, the Heart Rhythm Society, the Asia Pacific Heart Rhythm Society, and the Latin American Heart Rhythm Society.

Safety and effectiveness of additional left atrial posterior wall ablation using pulsed field ablation for persistent and long-standing persistent atrial fibrillation patients

INTRODUCTION

The unique safety profile of pulsed field ablation (PFA) has made pulmonary vein isolation (PVI) + left atrial posterior wall (LAPW) ablation promising for treating persistent atrial fibrillation (PerAF). The goal of this study was to assess long-term freedom from atrial fibrillation, atrial flutter, and atrial tachycardia (AF/AFL/AT), as well as the safety and feasibility of LAPW PFA using multipolar, pentaspline Farawave catheter.

METHODS

Retrospective observational study at a single institution. Data for 94 patients were collected from a prespecified intraprocedural registry. The long-term AF/AFL/AT recurrence assessment was based on an analysis of medical history; 24-h Holter ECGs at 3, 6, and 12 months postablation; and 12-lead ECGs recorded during symptomatic episodes or visits.

RESULTS

Half of the patients had ls-PerAF, and half had a history of catheter ablation-mostly RF PVI. The acute ablation success rate was 100%, and the primary safety outcome was observed in 2 patients. Fifty patients experienced AF/AFL/AT recurrence (54.3%). An increase in LAPW low-voltage areas and AF classification were associated with arrhythmia recurrence. After a median follow-up of 13 months, the Kaplan‒Meier estimated median time free of AF/AFL/AT after a single procedure was 14.7 months.

CONCLUSION

PFA PVI + PWA had the best outcome in perAF patients without extensive LA fibrosis. AF recurrence was paroxysmal in significant part of the cohort. The addition of PWA to PVI using multipolar PFA was safe and did not significantly influence the transpired ablation time.

2024 European Heart Rhythm Association/Heart Rhythm Society/Asia Pacific Heart Rhythm Society/Latin American Heart Rhythm Society expert consensus statement on catheter and surgical ablation of atrial fibrillation

In the last three decades, ablation of atrial fibrillation (AF) has become an evidence-based safe and efficacious treatment for managing the most common cardiac arrhythmia. In 2007, the first joint expert consensus document was issued, guiding healthcare professionals involved in catheter or surgical AF ablation. Mounting research evidence and technological advances have resulted in a rapidly changing landscape in the field of catheter and surgical AF ablation, thus stressing the need for regularly updated versions of this partnership which were issued in 2012 and 2017. Seven years after the last consensus, an updated document was considered necessary to define a contemporary framework for selection and management of patients considered for or undergoing catheter or surgical AF ablation. This consensus is a joint effort from collaborating cardiac electrophysiology societies, namely the European Heart Rhythm Association, the Heart Rhythm Society (HRS), the Asia Pacific HRS, and the Latin American HRS.

Practical approach for atrial cardiomyopathy characterization in patients with atrial fibrillation

Atrial fibrillation (AF) causes progressive structural and electrical changes in the atria that can be summarized within the general concept of atrial remodeling. In parallel, other clinical characteristics and comorbidities may also affect atrial tissue properties and make the atria susceptible to AF initiation and its long-term persistence. Overall, pathological atrial changes lead to atrial cardiomyopathy with important implications for rhythm control. Although there is general agreement on the role of the atrial substrate for successful rhythm control in AF, the current classification oversimplifies clinical management. The classification uses temporal criteria and does not establish a well-defined strategy to characterize the individual-specific degree of atrial cardiomyopathy. Better characterization of atrial cardiomyopathy may improve the decision-making process on the most appropriate therapeutic option. We review current scientific evidence and propose a practical characterization of the atrial substrate based on 3 evaluation steps starting with a clinical evaluation (step 1), then assess outpatient complementary data (step 2), and finally include information from advanced diagnostic tools (step 3). The information from each of the steps or a combination thereof can be used to classify AF patients in 4 stages of atrial cardiomyopathy, which we also use to estimate the success on effective rhythm control.

Catheter ablation for atrial fibrillation in patients with significant mitral regurgitation: A systematic review and meta-analysis

BACKGROUND

Atrial fibrillation (AF) is commonly associated with cardiac structural abnormalities including mitral regurgitation (MR). Contemporary guidelines recommend consideration of early rhythm control strategies including catheter ablation (CA) for AF. However, the long-term efficacy of CA is highly variable across studies and patient populations, and the effect of coexisting MR on AF recurrence remains unclear.

OBJECTIVE

A systematic review and meta-analysis was performed to determine the impact of significant MR (defined as ≥moderate) on AF recurrence rate after CA and whether CA for AF is associated with significant changes in the severity of MR.

METHODS

A systematic search of PubMed, Embase, Web of Science, and Cochrane databases for all English-language studies published to December 31, 2023, was performed.

RESULTS

A total of 17 studies (N = 2624 patients) were retained for meta-analysis. The pooled recurrence proportion of AF after CA in patients with baseline significant MR was 36% (95% CI, 27%-46%) compared with 27% (14%-41%) in patients without. The pooled hazard ratio (95% CI) for AF recurrence after CA in the presence of significant MR was 2.47 (1.52-4.01; P < .001; Egger test P value, .0583). The pooled proportion of patients who witnessed MR improvement to nonsignificant (ie,

CONCLUSION

Baseline significant MR was independently predictive of AF recurrence rate after CA. Despite the increased AF recurrence rates after CA associated with significant MR, CA with maintenance of sinus rhythm appeared to improve the severity of MR, suggesting a possible induction of reverse positive atrial and mitral valvular remodeling.

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Key Words

• Atrial fibrillation
• Catheter ablation
• Mitral regurgitation
• Pulmonary vein isolation
• Review

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MESH Headings Collapse

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Affiliation(s)

Ross A Okazaki Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts
Lillian C Flashner Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts
Scott Kinlay Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Harvard Medical School, Boston, Massachusetts; Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
Adelqui O Peralta Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Harvard Medical School, Boston, Massachusetts
Peter S Hoffmeister Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Harvard Medical School, Boston, Massachusetts
Hirad Yarmohammadi Department of Medicine, Columbia University, New York, New York
Jacob Joseph Department of Medicine, Brown University, Providence, Rhode Island; Department of Medicine, VA Providence Healthcare System, Providence, Rhode Island
Matthew F Yuyun Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Harvard Medical School, Boston, Massachusetts.

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Association of atrial mechanical dispersion with atrial fibrillation recurrence following catheter ablation: results of the ASTRA-AF pilot study

AIMS

For patients with symptomatic drug-refractory atrial fibrillation (AF), catheter ablation to achieve rhythm control is an important therapeutic option. The atrial mechanical dispersion measured as standard deviation of the time to peak strain (SD-TPS) is associated with the risk of AF recurrence following catheter ablation.

METHODS

The study cohort prospectively enrolled n = 132 consecutive patients with paroxysmal (n = 88) or persistent AF (n = 44) presenting for de novo pulmonary vein isolation (PVI) and followed for 1 year. We related left atrial (LA) volume, LA ejection fraction, SD-TPS, and global longitudinal strain of the left ventricle and clinical variables (sex, age, and type of AF) to AF recurrence.

RESULTS

Kaplan-Meier curves showed higher AF recurrence rate with an increase of SD-TPS with the calculated cut-off of 38.6 ms. Uni- and multivariable Cox regression analysis could show that SD-TPS had the highest relevance regarding AF recurrence with a HR of 1.05 (95% CI, 1.01; 1.09, p = 0.01) and HR of 1.05 (95% CI, 1.01; 1.09, p = 0.02) per 10 ms increase. In the additional analyses for the model including the clinical variables age, sex, and type of AF with paroxysmal or persisting AF, SD-TPS did only show a trend and after adjusting for covariates, SD-TPS showed a HR of 1.04 (95% CI, 0.99; 1.09, p = 0.09) per 10 ms increase.

CONCLUSION

Atrial mechanical dispersion was associated with recurrent AF.

[Cluster Analysis and Ablation Success Rate in Atrial Fibrillation Patients Undergoing Catheter Ablation]

Objective

Atrial fibrillation (AF) is a disease of high heterogeneity, and the association between AF phenotypes and the outcome of different catheter ablation strategies remains unclear. Conventional classification of AF (e.g. according to duration, atrial size, and thromboembolism risk) fails to provide reference for the optimal stratification of the prognostic risks or to guide individualized treatment plan. In recent years, research on machine learning has found that cluster analysis, an unsupervised data-driven approach, can uncover the intrinsic structure of data and identify clusters of patients with pathophysiological similarity. It has been demonstrated that cluster analysis helps improve the characterization of AF phenotypes and provide valuable prognostic information. In our cohort of AF inpatients undergoing radiofrequency catheter ablation, we used unsupervised cluster analysis to identify patient subgroups, to compare them with previous studies, and to evaluate their association with different suitable ablation patterns and outcomes.

Methods

The participants were AF patients undergoing radiofrequency catheter ablation at West China Hospital between October 2015 and December 2017. All participants were aged 18 years or older. They underwent radiofrequency catheter ablation during their hospitalization. They completed the follow-up process under explicit informed consent. Patients with AF of a reversible cause, severe mitral stenosis or prosthetic heart valve, congenital heart disease, new-onset acute coronary syndrome within three months prior to the surgery, or a life expectancy less than 12 months were excluded according to the exclusion criteria. The cohort consisted of 1102 participants with paroxysmal or persistent/long-standing persistent AF. Data on 59 variables representing demographics, AF type, comorbidities, therapeutic history, vital signs, electrocardiographic and echocardiographic findings, and laboratory findings were collected. Overall, data for the variables were rarely missing (<5%), and multiple imputation was used for correction of missing data. Follow-up surveys were conducted through outpatient clinic visits or by telephone. Patients were scheduled for follow-up with 12-lead resting electrocardiography and 24-hours Holter monitoring at 3 months and 6 months after the ablation procedure. Early ablation success was defined as the absence of documented AF, atrial flutter, or atrial tachycardia >30 seconds at 6-month follow-up. Hierarchical clustering was performed on the 59 baseline variables. All characteristic variables were standardized to have a mean of zero and a standard deviation of one. Initially, each patient was regarded as a separate cluster, and the distance between these clusters was calculated. Then, the Ward minimum variance method of clustering was used to merge the pair of clusters with the minimum total variance. This process continued until all patients formed one whole cluster. The "NbClust" package in R software, capable of calculating various statistical indices, including pseudo t2 index, cubic clustering criterion, silhouette index etc, was applied to determine the optimal number of clusters. The most frequently chosen number of clusters by these indices was selected. A heatmap was generated to illustrate the clinical features of clusters, while a tree diagram was used to depict the clustering process and the heterogeneity among clusters. Ablation strategies were compared within each cluster regarding ablation efficacy.

Results

Five statistically driven clusters were identified: 1) the younger age cluster (n=404), characterized by the lowest prevalence of cardiovascular and cerebrovascular comorbidities but the highest prevalence of obstructive sleep apnea syndrome (14.4%); 2) a cluster of elderly adults with chronic diseases (n=438), the largest cluster, showing relatively higher rates of hypertension, diabetes, stroke, and chronic obstructive pulmonary disease; 3) a cluster with high prevalence of sinus node dysfunction (n=160), with patients showing the highest prevalence of sick sinus syndrome and pacemaker implantation; 4) the heart failure cluster (n=80), with the highest prevalence of heart failure (58.8%) and persistent/long-standing persistent AF (73.7%); 5) prior coronary artery revascularization cluster (n=20), with patients of the most advanced age (median: 69.0 years old) and predominantly male patients, all of whom had prior myocardial infarction and coronary artery revascularization. Patients in cluster 2 achieved higher early ablation success with pulmonary veins isolation alone compared to extensive ablation strategies (79.6% vs. 66.5%; odds ratio [OR]=1.97, 95% confidence interval [CI]: 1.28-3.03). Although extensive ablation strategies had a slightly higher success rate in the heart failure group, the difference was not statistically significant.

Conclusions

This study provided a unique classification of AF patients undergoing catheter ablation by cluster analysis. Age, chronic disease, sinus node dysfunction, heart failure and history of coronary artery revascularization contributed to the formation of the five clinically relevant subtypes. These subtypes showed differences in ablation success rates, highlighting the potential of cluster analysis in guiding individualized risk stratification and treatment decisions for AF patients.

Identification of Plasmatic MicroRNA-206 as New Predictor of Early Recurrence of Atrial Fibrillation After Catheter Ablation Using Next-generation Sequencing

BACKGROUND

Catheter ablation (CA) of atrial fibrillation (AF) is indicated in patients with recurrent and symptomatic AF episodes. Despite the strict inclusion/exclusion criteria, AF recurrence after CA remains high. Identification of a novel biomarker that would predict AF recurrence would help to stratify the patients. The aim of the study was to seek novel biomarkers among the plasmatic microRNAs (miRNAs, miRs).

METHODS

A prospective monocentric study was conducted. A total of 49 consecutive AF patients indicated for CA were included. Blood sampling was performed prior to CA. RNA was isolated from plasma using commercial kits. In the exploration phase, small RNA sequencing was performed in ten AF patients (five with and five without AF recurrence) using Illumina instrument. In the validation phase, levels of selected miRNAs were determined using quantitative reverse transcription polymerase chain reaction (qRT-PCR) in all participants.

RESULTS

Altogether, 22 miRNAs were identified as altered between the groups by next-generation sequencing (using the DESeq2 algorithm). Using qRT-PCR, levels of the five most altered miRNAs (miR-190b/206/326/505-5p/1296-5p) were verified in the whole cohort. Plasma levels of hsa-miR-206 were significantly higher in patients with early (within 6 months) AF recurrence and showed an increase of risk recurrence,2.65 times by every increase in its level by 1 unit in the binary logistic regression.

CONCLUSION

We have identified a set of 22 plasmatic miRNAs that differ between the patients with and without AF recurrence after CA and confirmed hsa-miR-206 as a novel miRNA associated with early AF recurrence. Results shall be verified in a larger independent cohort.

Use of artificial intelligence and I-Score for prediction of recurrence before catheter ablation of atrial fibrillation

BACKGROUND

Based solely on pre-ablation characteristics, previous risk scores have demonstrated variable predictive performance. This study aimed to predict the recurrence of AF after catheter ablation by using artificial intelligence (AI)-enabled pre-ablation computed tomography (PVCT) images and pre-ablation clinical data.

METHODS

A total of 638 drug-refractory paroxysmal atrial fibrillation (AF) patients undergone ablation were recruited. For model training, we used left atria (LA) acquired from pre-ablation PVCT slices (126,288 images). A total of 29 clinical variables were collected before ablation, including baseline characteristics, medical histories, laboratory results, transthoracic echocardiographic parameters, and 3D reconstructed LA volumes. The I-Score was applied to select variables for model training. For the prediction of one-year AF recurrence, PVCT deep-learning and clinical variable machine-learning models were developed. We then applied machine learning to ensemble the PVCT and clinical variable models.

RESULTS

The PVCT model achieved an AUC of 0.63 in the test set. Various combinations of clinical variables selected by I-Score can yield an AUC of 0.72, which is significantly better than all variables or features selected by nonparametric statistics (AUCs of 0.66 to 0.69). The ensemble model (PVCT images and clinical variables) significantly improved predictive performance up to an AUC of 0.76 (sensitivity of 86.7% and specificity of 51.0%).

CONCLUSIONS

Before ablation, AI-enabled PVCT combined with I-Score features was applicable in predicting recurrence in paroxysmal AF patients. Based on all possible predictors, the I-Score is capable of identifying the most influential combination.

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.

Predicting Adverse Outcomes Following Catheter Ablation Treatment for Atrial Flutter/Fibrillation

BACKGROUND & AIM

To develop prognostic survival models for predicting adverse outcomes after catheter ablation treatment for non-valvular atrial fibrillation (AF) and/or atrial flutter (AFL).

METHODS

We used a linked dataset including hospital administrative data, prescription medicine claims, emergency department presentations, and death registrations of patients in New South Wales, Australia. The cohort included patients who received catheter ablation for AF and/or AFL. Traditional and deep survival models were trained to predict major bleeding events and a composite of heart failure, stroke, cardiac arrest, and death.

RESULTS

Out of a total of 3,285 patients in the cohort, 177 (5.3%) experienced the composite outcome-heart failure, stroke, cardiac arrest, death-and 167 (5.1%) experienced major bleeding events after catheter ablation treatment. Models predicting the composite outcome had high-risk discrimination accuracy, with the best model having a concordance index >0.79 at the evaluated time horizons. Models for predicting major bleeding events had poor risk discrimination performance, with all models having a concordance index <0.66. The most impactful features for the models predicting higher risk were comorbidities indicative of poor health, older age, and therapies commonly used in sicker patients to treat heart failure and AF and AFL.

DISCUSSION

Diagnosis and medication history did not contain sufficient information for precise risk prediction of experiencing major bleeding events. Predicting the composite outcome yielded promising results, but future research is needed to validate the usefulness of these models in clinical practice.

CONCLUSIONS

Machine learning models for predicting the composite outcome have the potential to enable clinicians to identify and manage high-risk patients following catheter ablation for AF and AFL proactively.

2024 European Heart Rhythm Association/Heart Rhythm Society/Asia Pacific Heart Rhythm Society/Latin American Heart Rhythm Society expert consensus statement on catheter and surgical ablation of atrial fibrillation

In the last three decades, ablation of atrial fibrillation (AF) has become an evidence-based safe and efficacious treatment for managing the most common cardiac arrhythmia. In 2007, the first joint expert consensus document was issued, guiding healthcare professionals involved in catheter or surgical AF ablation. Mounting research evidence and technological advances have resulted in a rapidly changing landscape in the field of catheter and surgical AF ablation, thus stressing the need for regularly updated versions of this partnership which were issued in 2012 and 2017. Seven years after the last consensus, an updated document was considered necessary to define a contemporary framework for selection and management of patients considered for or undergoing catheter or surgical AF ablation. This consensus is a joint effort from collaborating cardiac electrophysiology societies, namely the European Heart Rhythm Association, the Heart Rhythm Society, the Asia Pacific Heart Rhythm Society, and the Latin American Heart Rhythm Society .

Recurrence After Atrial Fibrillation Ablation and Investigational Biomarkers of Cardiac Remodeling

BACKGROUND

Recurrence after atrial fibrillation (AF) ablation remains common. We evaluated the association between recurrence and levels of biomarkers of cardiac remodeling, and their ability to improve recurrence prediction when added to a clinical prediction model.

METHODS AND RESULTS

Blood samples collected before de novo catheter ablation were analyzed. Levels of bone morphogenetic protein-10, angiopoietin-2, fibroblast growth factor-23, insulin-like growth factor-binding protein-7, myosin-binding protein C3, growth differentiation factor-15, interleukin-6, N-terminal pro-brain natriuretic peptide, and high-sensitivity troponin T were measured. Recurrence was defined as ≥30 seconds of an atrial arrhythmia 3 to 12 months postablation. Multivariable logistic regression was performed using biomarker levels along with clinical covariates: APPLE score (Age >65 years, Persistent AF, imPaired eGFR [<60 ml/min/1.73m2], LA diameter ≥43 mm, EF <50%; which includes age, left atrial diameter, left ventricular ejection fraction, persistent atrial fibrillation, and estimated glomerular filtration rate), preablation rhythm, sex, height, body mass index, presence of an implanted continuous monitor, year of ablation, and additional linear ablation. A total of 1873 participants were included. A multivariable logistic regression showed an association between recurrence and levels of angiopoietin-2 (odds ratio, 1.08 [95% CI, 1.02-1.15], P=0.007) and interleukin-6 (odds ratio, 1.02 [95% CI, 1.003-1.03]; P=0.02). The area under the receiver operating characteristic curve of a model that only contained clinical predictors was 0.711. The addition of any of the 9 studied biomarkers to the predictive model did not result in a statistically significant improvement in the area under the receiver operating characteristic curve.

CONCLUSIONS

Higher angiopoietin-2 and interleukin-6 levels were associated with recurrence after atrial fibrillation ablation in multivariable modeling. However, the addition of biomarkers to a clinical prediction model did not significantly improve recurrence prediction.

Evaluation of the effectiveness and safety of a novel substrate-based radiofrequency ablation for persistent atrial fibrillation: a prospective, randomised, parallel-controlled, single-blinded study protocol

INTRODUCTION

Pulmonary vein isolation (PVI) is the cornerstone of radiofrequency (RF) ablation for atrial fibrillation (AF). However, a single ablation strategy does not always achieve the desired therapeutic effect in all patients with persistent AF, and individualised strategies are required for different clinical characteristics.

METHODS AND ANALYSIS

This study aimed to determine the optimal catheter ablation strategy for persistent AF by comparing the efficacy of PVI and BCXL (BC: big circles encircling pulmonary vein isolation; XL: unfixed number of lines based on the left atrial substrate). The BCXL-AF study (clinical trial no. ChiCTR2200067081) was designed as a prospective, randomised, parallel-controlled, single-blinded clinical trial. Overall, 400 patients with persistent AF were randomised in a 1:1 ratio into PVI-only and BCXL-individualised ablation groups. Patients randomised to the individualised ablation group will be further categorised into risk strata according to their clinical condition using the actual ablation method determined by the strata. Seven postoperative visits were conducted from discharge to 24 months of age. The primary observation endpoint will be the incidence of atrial tachyarrhythmia (including AF, atrial flutter and atrial tachycardia with a duration of ≥30 s) without using antiarrhythmic drugs after a blank period of 3 months following a single ablation procedure. The BCXL-AF study will assess an optimal approach for persistent AF RF ablation and evaluate the effectiveness of individualised RF ablation strategies in reducing the recurrence rate of AF.

ETHICS AND DISSEMINATION

The study protocol was reviewed, and ethical approval was obtained from the Army Medical University Human Ethics Committee (approval number: 2022-484-01). All the participants provided written informed consent. This study was conducted according to the principles of the Declaration of Helsinki and its amendments. The results of this study will be disseminated through manuscript publication and conference presentations.

TRIAL REGISTRATION NUMBER

ChiCTR2200067081.

Combination of frequency- and time-domain characteristics of the fibrillatory waves for enhanced prediction of persistent atrial fibrillation recurrence after catheter ablation

Catheter ablation (CA) remains the cornerstone alternative to cardioversion for sinus rhythm (SR) restoration in patients with atrial fibrillation (AF). Unfortunately, despite the last methodological and technological advances, this procedure is not consistently effective in treating persistent AF. Beyond introducing new indices to characterize the fibrillatory waves (f-waves) recorded through the preoperative electrocardiogram (ECG), the aim of this study is to combine frequency- and time-domain features to improve CA outcome prediction and optimize patient selection for the procedure, given the absence of any study that jointly analyzes information from both domains. Precisely, the f-waves of 151 persistent AF patients undergoing their first CA procedure were extracted from standard V1 lead. Novel spectral and amplitude features were derived from these waves and combined through a machine learning algorithm to anticipate the intervention mid-term outcome. The power rate index (φ), which estimates the power of the harmonic content regarding the dominant frequency (DF), yielded the maximum individual discriminant ability of 64% to discern between individuals who experienced a recurrence of AF and those who sustained SR after a 9-month follow-up period. The predictive accuracy was improved up to 78.5% when this parameter φ was merged with the amplitude spectrum area in the DF bandwidth (A M S A L F ) and the normalized amplitude of the f-waves into a prediction model based on an ensemble classifier, built by random undersampling boosting of decision trees. This outcome suggests that the synthesis of both spectral and temporal features of the f-waves before CA might enrich the prognostic knowledge of this therapy for persistent AF patients.

Disturbed atrial metabolism, shear stress, and cardiac load contribute to atrial fibrillation after ablation: AXAFA biomolecule study

AIMS

Different disease processes can combine to cause atrial fibrillation (AF). Their contribution to recurrent AF after ablation in patients is not known. Cardiovascular processes associated with recurrent AF after AF ablation were determined by quantifying biomolecules related to inflammation, metabolism, proliferation, fibrosis, shear stress, atrial pressure, and others in the AXAFA biomolecule study.

METHODS AND RESULTS

Twelve circulating cardiovascular biomolecules (ANGPT2, BMP10, CA125, hsCRP, ESM1, FABP3, FGF23, GDF15, IGFBP7, IL6, NT-proBNP, and hsTnT) were quantified in plasma samples obtained prior to a first AF ablation using high-throughput, high-precision assays. Cox regression was used to identify biomolecules associated with recurrent AF during the first 3 months after AF ablation. In 433 patients (64 years [58, 70]; 33% women), baseline concentrations of ANGPT2, BMP10, hsCRP, FGF23, FABP3, GDF15, and NT-proBNP were elevated in patients with recurrent AF (120/433; 28%). After adjustment for 11 clinical features and randomized treatment, elevated NT-proBNP [hazard ratio (HR) 1.58, 95% confidence interval (1.29, 1.94)], ANGPT2 [HR 1.37, (1.12, 1.67)], and BMP10 [HR 1.24 (1.02, 1.51)] remained associated with recurrent AF. Concentrations of ANGPT2, BMP10, and NT-proBNP decreased in patients who remained arrhythmia free, but not in patients with recurrent AF, highlighting their connection to AF. The other eight biomarkers showed unchanged concentrations.

CONCLUSION

Elevated concentrations of ANGPT2, BMP10, and NT-proBNP are associated with recurrent AF after a first AF ablation, suggesting that processes linked to disturbed cardiomyocyte metabolism, altered atrial shear stress, and increased load contribute to AF after AF ablation in patients.

Hybrid Endo-Epicardial Therapies for Advanced Atrial Fibrillation

Atrial fibrillation (AF) is a growing health problem that increases morbidity and mortality, and in most patients progresses to more advanced diseases over time. Recent research has examined the underlying mechanisms, risk factors, and progression of AF, leading to updated AF disease classification schemes. Although endocardial catheter ablation is effective for early-stage paroxysmal AF, it consistently achieves suboptimal outcomes in patients with advanced AF. Identification of the factors that lead to the increased risk of treatment failure in advanced AF has spurred the development and adoption of hybrid ablation therapies and collaborative heart care teams that result in higher long-term arrhythmia-free survival. Patients with non-paroxysmal AF, atrial remodeling, comorbidities, or AF otherwise deemed difficult to treat may find hybrid treatment to be the most effective option. Future research of hybrid therapies in advanced AF patient populations, including those with dual diagnoses, may provide further evidence establishing the safety and efficacy of hybrid endo-epicardial ablation as a first line treatment.

Identification of recurrent atrial fibrillation using natural language processing applied to electronic health records

AIMS

This study aimed to develop and apply natural language processing (NLP) algorithms to identify recurrent atrial fibrillation (AF) episodes following rhythm control therapy initiation using electronic health records (EHRs).

METHODS AND RESULTS

We included adults with new-onset AF who initiated rhythm control therapies (ablation, cardioversion, or antiarrhythmic medication) within two US integrated healthcare delivery systems. A code-based algorithm identified potential AF recurrence using diagnosis and procedure codes. An automated NLP algorithm was developed and validated to capture AF recurrence from electrocardiograms, cardiac monitor reports, and clinical notes. Compared with the reference standard cases confirmed by physicians' adjudication, the F-scores, sensitivity, and specificity were all above 0.90 for the NLP algorithms at both sites. We applied the NLP and code-based algorithms to patients with incident AF (n = 22 970) during the 12 months after initiating rhythm control therapy. Applying the NLP algorithms, the percentages of patients with AF recurrence for sites 1 and 2 were 60.7% and 69.9% (ablation), 64.5% and 73.7% (cardioversion), and 49.6% and 55.5% (antiarrhythmic medication), respectively. In comparison, the percentages of patients with code-identified AF recurrence for sites 1 and 2 were 20.2% and 23.7% for ablation, 25.6% and 28.4% for cardioversion, and 20.0% and 27.5% for antiarrhythmic medication, respectively.

CONCLUSION

When compared with a code-based approach alone, this study's high-performing automated NLP method identified significantly more patients with recurrent AF. The NLP algorithms could enable efficient evaluation of treatment effectiveness of AF therapies in large populations and help develop tailored interventions.

Usefulness of risk scores and predictors of atrial fibrillation recurrence after elective electrical cardioversion

INTRODUCTION

Electrical cardioversion (ECV) is a frequently used procedure for restoring sinus rhythm in atrial fibrillation (AF); however, the rate of recurrence is high. The identification of patients at high risk of recurrence could influence the decision-making process. The present study evaluates the predictive value of risk scores in atrial fibrillation recurrence after elective electrical cardioversion.

METHODS

Unicentric, observational, and prospective study of adult patients who have undergone an elective ECV as rhythm control strategy between July 2017 and September 2022.

RESULTS

From the 283 analyzed patients (mean age 63.95 ± 10.76212, 74.9% male); 99 had paroxysmal AF (35%) and 159 (59%) presented AF recurrence during a follow-up of 6 months. In patients with post-ECV AF recurrence, the period of time from diagnosis until the performance of the procedure was longer (393 ± 891 vs. 195 ± 527, p = .02). No paroxysmal AF (71.3% vs. 57.8%, p = .02) and LA dilatation with >40 mL/m2 (35.9% vs. 23.3%, p = .02) volumes were more frequent within these patients. AF recurrence was more frequent in patients who had previous ECV (HR = 1.32; 95% CI: 1.12-2.35; p = .01) and more than 1 shock to recover sinus rhythm (HR = 1.62; 95% CI: 1.07-1.63; p = .01). The SLAC, ALARMEc, ATLAS, and CAAP-AF scores were statistically significant, although with a moderate predictive capacity for post-ECV recurrence.

CONCLUSIONS

Risk scores analyzed showed a modest value predicting AF recurrence after ECV. Previous ECV, and greater difficulty in restoring SR were independent predictors of recurrence.

Impact of chronic obstructive pulmonary disease in patients with atrial fibrillation: an analysis from the GLORIA-AF registry

AIMS

Chronic obstructive pulmonary disease (COPD) may influence management and prognosis of atrial fibrillation (AF), but this relationship has been scarcely explored in contemporary global cohorts. We aimed to investigate the association between AF and COPD, in relation to treatment patterns and major outcomes.

METHODS AND RESULTS

From the prospective, global GLORIA-AF registry, we analysed factors associated with COPD diagnosis, as well as treatment patterns and risk of major outcomes in relation to COPD. The primary outcome was the composite of all-cause death and major adverse cardiovascular events (MACEs). A total of 36 263 patients (mean age 70.1 ± 10.5 years, 45.2% females) were included; 2,261 (6.2%) had COPD. The prevalence of COPD was lower in Asia and higher in North America. Age, female sex, smoking, body mass index, and cardiovascular comorbidities were associated with the presence of COPD. Chronic obstructive pulmonary disease was associated with higher use of oral anticoagulant (OAC) [adjusted odds ratio (aOR) and 95% confidence interval (CI): 1.29 (1.13-1.47)] and higher OAC discontinuation [adjusted hazard ratio (aHR) and 95% CI: 1.12 (1.01-1.25)]. Chronic obstructive pulmonary disease was associated with less use of beta-blocker [aOR (95% CI): 0.79 (0.72-0.87)], amiodarone and propafenone, and higher use of digoxin and verapamil/diltiazem. Patients with COPD had a higher hazard of primary composite outcome [aHR (95% CI): 1.78 (1.58-2.00)]; no interaction was observed regarding beta-blocker use. Chronic obstructive pulmonary disease was also associated with all-cause death [aHR (95% CI): 2.01 (1.77-2.28)], MACEs [aHR (95% CI): 1.41 (1.18-1.68)], and major bleeding [aHR (95% CI): 1.48 (1.16-1.88)].

CONCLUSION

In AF patients, COPD was associated with differences in OAC treatment and use of other drugs; Patients with AF and COPD had worse outcomes, including higher mortality, MACE, and major bleeding.

Novel Entropy-Based Metrics for Long-Term Atrial Fibrillation Recurrence Prediction Following Surgical Ablation: Insights from Preoperative Electrocardiographic Analysis

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia often treated concomitantly with other cardiac interventions through the Cox-Maze procedure. This highly invasive intervention is still linked to a long-term recurrence rate of approximately 35% in permanent AF patients. The aim of this study is to preoperatively predict long-term AF recurrence post-surgery through the analysis of atrial activity (AA) organization from non-invasive electrocardiographic (ECG) recordings. A dataset comprising ECGs from 53 patients with permanent AF who had undergone Cox-Maze concomitant surgery was analyzed. The AA was extracted from the lead V1 of these recordings and then characterized using novel predictors, such as the mean and standard deviation of the relative wavelet energy (RWEm and RWEs) across different scales, and an entropy-based metric that computes the stationary wavelet entropy variability (SWEnV). The individual predictors exhibited limited predictive capabilities to anticipate the outcome of the procedure, with the SWEnV yielding a classification accuracy (Acc) of 68.07%. However, the assessment of the RWEs for the seventh scale (RWEs7), which encompassed frequencies associated with the AA, stood out as the most promising individual predictor, with sensitivity (Se) and specificity (Sp) values of 80.83% and 67.09%, respectively, and an Acc of almost 75%. Diverse multivariate decision tree-based models were constructed for prediction, giving priority to simplicity in the interpretation of the forecasting methodology. In fact, the combination of the SWEnV and RWEs7 consistently outperformed the individual predictors and excelled in predicting post-surgery outcomes one year after the Cox-Maze procedure, with Se, Sp, and Acc values of approximately 80%, thus surpassing the results of previous studies based on anatomical predictors associated with atrial function or clinical data. These findings emphasize the crucial role of preoperative patient-specific ECG signal analysis in tailoring post-surgical care, enhancing clinical decision making, and improving long-term clinical outcomes.

New Score for Predicting Results after Catheter Ablation for Atrial Fibrillation: VAT-DHF

INTRODUCTION

Catheter ablation (CA) for atrial fibrillation (AF) has been proven to have the highest efficacy in maintaining sinus rhythm. Several studies have proposed different scores for predicting post-procedural success, but most have not been validated in prospective cohorts. Further research is required to determine the optimal formulae.

PURPOSE

This study aimed to identify independent predictors of AF recurrence after CA and develop a composite score.

METHODS

Consecutive patients with persistent and paroxysmal AF who underwent CA were retrospectively analyzed. The independent predictors of recurrence were used to create a new predictive score.

RESULTS

The cohort included 263 patients with a follow-up of 37.6 ± 23.4 months. Persistent AF, f-waves < 0.1 mV, indexed left atrium volume, the presence of type 2 diabetes, and smaller height were independent predictors of recurrence and were used to create a new scoring model, VAT-DHF (V = Volume, AT = AF Type, D = Diabetes, H = Height, F = f waves). The ROC curve for this new score showed an AUC of 0.869, p < 0.0001, 95% CI [0.802-0.936], while those for APPLE and CHA2DS2-VASc showed an AUC of 0.765, 95% CI [0.637-0.893] and an AUC of 0.655, 95% CI [0.580-0.730], respectively. Patients who had a VAT-DHF score between 0 and 3.25, 3.25 and 6, and ≥6, had success rates of 95.7%, 76.3%, and 25% (p < 0.0001), respectively.

CONCLUSIONS

The novel VAT-DHF score is easy to calculate and may be a useful clinical tool for identifying patients with a low, intermediate, or high risk of AF recurrence after CA.

Pulmonary vein isolation by visually guided laser balloon ablation: single-center 5-year follow-up results

BACKGROUND

Visually guided laser balloon (VGLB) ablation is a balloon-based treatment for atrial fibrillation (AF) that uses a titratable laser energy source to perform pulmonary vein isolation (PVI), allowing for real-time visualization of target tissue and ablation lesions through an endoscopic camera. Few long-term data on this technique are currently available. This report presents acute efficacy, procedural data, complication rates, and long-term AF-free survival up to 5 years post-ablation.

METHODS

In this single-center, retrospective, observational report, 152 patients (72.4% male, mean age 60.6 ± 9.7 years, 62.5% paroxysmal AF, 598 pulmonary veins in total) treated with the first-generation VGLB system between 2014 and 2016 were included for analysis. AF ablation consisted of PVI only.

RESULTS

Acute PVI was achieved in 98.2% of veins, with first-pass isolation in 92.5%. Procedure duration of 129 min [IQR 113-150], fluoroscopy time of 15 min [IQR 11-20], and dose area product of 5016 mGy·cm2 [IQR 3603-8711] were recorded. During a median follow-up of 51 months [IQR 45-57], 74.3% of patients remained free of AF (78.8% for paroxysmal and 65.3% for persistent AF, p = 0.108). Freedom of AF at 1, 2, 3, and 4 years follow-up was 88.2%, 82.2%, 78.9%, and 74.8%, respectively. PV reconnections were identified in only 46.9% of redo procedures. The median number of PV reconnections during redo procedures was 0 [IQR 0-2]. Anti-arrhythmic drug use was significantly reduced after ablation (p < 0.001). The most commonly reported complications were minor vascular complications (4.6%) and transient phrenic nerve paralysis (3.3%).

CONCLUSIONS

First-generation VGLB ablation demonstrated high acute isolation rates, reasonable procedure times and low complication rates. Long-term freedom from AF was 78.8% for paroxysmal AF and 65.3% for persistent AF, performing PVI only.

Development and Validation of a Novel Prognostic Model Predicting the Atrial Fibrillation Recurrence Risk for Persistent Atrial Fibrillation Patients Treated with Nifekalant During the First Radiofrequency Catheter Ablation

BACKGROUND

This study aimed to establish and assess a prediction model for patients with persistent atrial fibrillation (AF) treated with nifekalant during the first radiofrequency catheter ablation (RFCA).

METHODS

In this study, 244 patients with persistent AF from January 17, 2017 to December 14, 2017, formed the derivation cohort, and 205 patients with persistent AF from December 15, 2017 to October 28, 2018, constituted the validation cohort. The least absolute shrinkage and selection operator regression was used for variable screening and the multivariable Cox survival model for nomogram development. The accuracy and discriminative capability of this predictive model were assessed according to discrimination (area under the curve [AUC]) and calibration. Clinical practical value was evaluated using decision curve analysis.

RESULTS

Body mass index, AF duration, sex, left atrial diameter, and the different responses after nifekalant administration were identified as AF recurrence-associated factors, all of which were selected for the nomogram. In the development and validation cohorts, the AUC for predicting 1-year AF-free survival was 0.863 (95% confidence interval (CI) 0.801-0.926) and 0.855 (95% CI 0.782-0.929), respectively. The calibration curves showed satisfactory agreement between the actual AF-free survival and the nomogram prediction in the derivation and validation cohorts. In both groups, the prognostic score enabled stratifying the patients into different AF recurrence risk groups.

CONCLUSIONS

This predictive nomogram can serve as a quantitative tool for estimating the 1-year AF recurrence risk for patients with persistent AF treated with nifekalant during the first RFCA.

Using machine learning to enhance prediction of atrial fibrillation recurrence after catheter ablation

Background

Traditional risk scores for recurrent atrial fibrillation (AF) following catheter ablation utilize readily available clinical and echocardiographic variables and yet have limited discriminatory capacity. Use of data from cardiac imaging and deep learning may help improve accuracy and prediction of recurrent AF after ablation.

Methods

We evaluated patients with symptomatic, drug-refractory AF undergoing catheter ablation. All patients underwent pre-ablation cardiac computed tomography (cCT). LAVi was computed using a deep-learning algorithm. In a two-step analysis, random survival forest (RSF) was used to generate prognostic models with variables of highest importance, followed by Cox proportional hazard regression analysis of the selected variables. Events of interest included early and late recurrence.

Results

Among 653 patients undergoing AF ablation, the most important factors associated with late recurrence by RSF analysis at 24 (+/-18) months follow-up included LAVi and early recurrence. In total, 5 covariates were identified as independent predictors of late recurrence: LAVi (HR per mL/m2 1.01 [1.01-1.02]; p < .001), early recurrence (HR 2.42 [1.90-3.09]; p < .001), statin use (HR 1.38 [1.09-1.75]; p = .007), beta-blocker use (HR 1.29 [1.01-1.65]; p = .043), and adjunctive cavotricuspid isthmus ablation [HR 0.74 (0.57-0.96); p = .02]. Survival analysis demonstrated that patients with both LAVi >66.7 mL/m2 and early recurrence had the highest risk of late recurrence risk compared with those with LAVi <66.7 mL/m2 and no early recurrence (HR 4.52 [3.36-6.08], p < .001).

Conclusions

Machine learning-derived, full volumetric LAVi from cCT is the most important pre-procedural risk factor for late AF recurrence following catheter ablation. The combination of increased LAVi and early recurrence confers more than a four-fold increased risk of late recurrence.

The higher recurrence rate after catheter ablation in younger patients with atrial fibrillation suggesting different pathophysiology

BACKGROUND

Young atrial fibrillation (AF) patients have been underrepresented in studies of radiofrequency catheter ablation (RFCA) and the outcome of RFCA has not been widely addressed. We investigated age-related differences in clinical features, the recurrence of atrial tachyarrhythmia, and its predictors of patients who underwent RFCA for AF.

METHODS

This is a multicenter prospective study of 2799 patients who underwent RFCA for AF in 2017-2020. The patients were divided into two groups - group A (age < 60 years, n = 1269) and group B (age ≥ 60 years, n = 1530) - and a recurrence of any atrial tachyarrhythmia 1 year after RFCA following a 90-day blanking period was compared.

RESULTS

The mean age was 51.6 ± 6.7 and 66.8 ± 5.2 years for groups A and B, respectively. Higher body mass index, smaller left atrium, and more prevalent cardiomyopathy and obstructive sleep apnea were observed in group A. Overall, 1-year atrial tachyarrhythmia-free survival was 85.6% and lower in young patients (83.1% in group A vs. 87.7% in group B, log-rank p < 0.01): adjusted hazard ratio (aHR) of recurrence (95% confidence interval (CI)), 1.45 (1.13-1.86) for group A compared to group B (p < 0.01). The association between younger age and higher recurrence was continuously observed in patients under 60 years. Any non-PV ablation was associated with a lower recurrence of atrial tachyarrhythmia in group B (aHR 0.68 (0.47-0.96), p < 0.05), but not in group A.

CONCLUSIONS

AF patients younger than 60 years had a higher 1-year AF recurrence after RFCA. Young AF patients might have distinctive pathophysiology of AF requiring more integrated management.

Machine learning model for predicting late recurrence of atrial fibrillation after catheter ablation

Late recurrence of atrial fibrillation (LRAF) in the first year following catheter ablation is a common and significant clinical problem. Our study aimed to create a machine-learning model for predicting arrhythmic recurrence within the first year since catheter ablation. The study comprised 201 consecutive patients (age: 61.8 ± 8.1; women 36%) with paroxysmal, persistent, and long-standing persistent atrial fibrillation (AF) who underwent cryoballoon (61%) and radiofrequency ablation (39%). Five different supervised machine-learning models (decision tree, logistic regression, random forest, XGBoost, support vector machines) were developed for predicting AF recurrence. Further, SHapley Additive exPlanations were derived to explain the predictions using 82 parameters based on clinical, laboratory, and procedural variables collected from each patient. The models were trained and validated using a stratified fivefold cross-validation, and a feature selection was performed with permutation importance. The XGBoost model with 12 variables showed the best performance on the testing cohort, with the highest AUC of 0.75 [95% confidence interval 0.7395, 0.7653]. The machine-learned model, based on the easily available 12 clinical and laboratory variables, predicted LRAF with good performance, which may provide a valuable tool in clinical practice for better patient selection and personalized AF strategy following the procedure.

Social determinants of health and recurrence of atrial fibrillation after catheter ablation: a Danish nationwide cohort study

AIMS

To examine the associations between three social determinants of health (SDOH) and recurrence of AF after ablation.

METHODS AND RESULTS

We selected patients who underwent a first ablation after an incident hospital diagnosis of AF between 2005 and 2018 from the entire Danish population. Educational attainment, family income, and whether the patient was living alone were assessed at the time of ablation. We used cause-specific proportional hazard models to estimate hazard ratios (HR) with 95% confidence interval (CI) adjusted for age and sex. In secondary analyses, we adjusted for comorbidities, antiarrhythmic medication, and prior electrical cardioversion.We selected 9728 patients (mean age 61 years, 70% men), and 5881 patients had AF recurrence over an average of 1.37 years after ablation (recurrence rate 325.7 (95% CI 317.6-334.2) per 1000 person-years). Lower education (HR 1.09 [1.02-1.17] and 1.07 [1.01-1.14] for lower and medium vs. higher), lower income [HR 1.14 (1.06-1.22) and 1.09 (1.03-1.17) for lower and medium vs. higher], and living alone [HR 1.07 (1.00-1.13)] were associated with increased rates of recurrence of AF. We found no evidence of interaction between sex or prior HF with SDOH. The association between family income and AF recurrence was stronger among patients < 65 years compared with those aged ≥ 65 years. The associations between SDOH and AF recurrence did not persist in the multivariable model.

CONCLUSION

AF was more likely to recur among patients with lower educational attainment, lower family income, or those living alone. Multidisciplinary efforts are needed to reduce socioeconomic inequity in the effect of ablation.

P-wave duration as a marker of atrial remodeling in patients referred to ablation for atrial fibrillation: A new stratification tool emerging?

Ablation of atrial fibrillation is one of the most widely applied invasive procedures in cardiovascular medicine, and populations with atrial fibrillation continuously rise. Recurrence rates are, however, consistently high, even in patients without severe comorbidities. Robust stratification algorithms to distinguish patients suitable for ablation are generally lacking. This is a fact caused by the inability to incorporate evidence of atrial remodeling and fibrosis, e.g., atrial remodeling, in the decision pathways. Cardiac magnetic resonance is a powerful tool in identifying fibrosis; however, it is costly and not routinely used. Electrocardiography has been generally underutilized in clinical practice during pre-ablative screening. One of the characteristics of the electrocardiogram that can give us valuable data depicting the existence and the extent of atrial remodeling and fibrosis is the duration of the P-wave. Currently, many studies support the implementation of P-wave duration in the routine practice of patient evaluation as a surrogate marker of existing atrial remodeling, that in turn predicts recurrence after ablation of atrial fibrillation. Further research is guaranteed to establish this electrocardiographic characteristic in our stratification quiver.

Clinical Outcomes and Predictors of Late Recurrence in Young Patients with Atrial Fibrillation after Catheter Ablation

Background

Catheter ablation (CA) is an established treatment for atrial fibrillation (AF), but the recurrence of AF is not neglected. Young patients with AF were generally more symptomatic and intolerant to long-term drug treatment. We aim to explore clinical outcomes and predictors of late recurrence (LR) in AF patients younger than 45 years after CA to better manage them.

Methods

We retrospectively studied 92 symptomatic AF patients who accepted CA from September 1, 2019, to August 31, 2021. Baseline clinical data (including N-terminal prohormone of brain natriuretic peptide, NT-proBNP), ablation outcomes, and follow-up outcomes were collected. Patients were followed up at 3, 6, 9, and 12 months. Follow-up data were available for 82/92 (89.1%) patients.

Results

One-year arrhythmia-free survival was 81.7% (67/82) in our study group. Major complications occurred in 3/82 (3.7%) patients with an acceptable rate. The value of ln(NT-proBNP) (P = 0.025, odds ratio [OR] = 1.977, 95% confidence interval [CI] 1.087-3.596) and a family history of AF (P = 0.041, HR = 9.269, 95% CI 1.097-78.295) could independently predict AF recurrence. The ROC analysis of ln(NT-proBNP) showed that NT-proBNP greater than 200.05 pg/ml (area under the curve: 0.772, 95% CI 0.642-0.902, P = 0.001, sensitivity 0.800, specificity 0.701) was the cut-off point for predicting late recurrence.

Conclusions

CA is a safe and effective treatment for AF patients younger than 45 years. Elevated NT-proBNP level and a family history of AF could be used as predictors for late recurrence in young patients. The result of this study may help us take more comprehensive management of those with high-recurrence risks to reduce disease burden and improve quality of life.

Left atrial appendage morphofunctional indices could be predictive of arrhythmia recurrence post-atrial fibrillation ablation: a meta-analysis

BACKGROUND

Left atrium changes are implicated in atrial fibrillation (AF) substrate and are predictive of AF outcomes. Left atrial appendage (LAA) is an integral component of left atrial structure and could be affected by atrial cardiomyopathy. We aimed to elucidate the association between LAA indices and late arrhythmia recurrence after atrial fibrillation catheter ablation (AFCA).

METHODS

The MEDLINE database, ClinicalTrials.gov, medRxiv and Cochrane Library were searched for studies evaluating LAA and late arrhythmia recurrence in patients undergoing AFCA. Data were pooled by meta-analysis using a random-effects model. The primary endpoint was pre-ablation difference in LAA anatomic or functional indices.

RESULTS

A total of 34 studies were found eligible and five LAA indices were analyzed. LAA ejection fraction and LAA emptying velocity were significantly lower in patients with AF recurrence post-ablation [SMD = - 0.66; 95% CI (- 1.01, - 0.32) and SMD = - 0.56; 95% CI (- 0.73, - 0.40) respectively] as compared to arrhythmia free controls. LAA volume and LAA orifice area were significantly higher in patients with AF recurrence post-ablation (SMD = 0.51; 95% CI 0.35-0.67, and SMD = 0.35; 95% CI 0.20-0.49, respectively) as compared to arrhythmia free controls. LAA morphology was not predictive of AF recurrence post-ablation (chicken wing morphology; OR 1.27; 95% CI 0.79-2.02). Moderate statistical heterogeneity and small case-control studies are the main limitations of our meta-analysis.

CONCLUSIONS

Our findings suggest that LAA ejection fraction, LAA emptying velocity, LAA orifice area and LAA volume differ between patients suffering from arrhythmia recurrence post-ablation and arrhythmia free counterparts, while LAA morphology is not predictive of AF recurrence.

Clinical Phenotypes and Atrial Fibrillation Recurrences after Catheter Ablation: An Unsupervised Cluster Analysis

Catheter ablation (CA) is a well-established treatment of atrial fibrillation (AF). Data-driven cluster analysis is able to better distinguish prognostically-relevant phenotype clusters among patients with AF. We performed a hierarchical cluster analysis in a cohort of AF patients undergoing a first CA and evaluate associations between identified clusters and recurrences of arrhythmia following ablation. The study included 209 AF patients treated with CA. 3 clusters with distinct characteristics were identified. Recurrences at one year occurred in 27.2% in Cluster 1, 43.2% in Cluster 2 and 60.9% in Cluster 3 (p<0.0001). Cluster classification was independently associated with arrhythmia recurrences (HR 1.58, 95% CI 1.01-2.49, p=0.046) after adjustment for age, CHA₂DS₂-VASc score, left atrial volume, type of atrial fibrillation and ejection fraction. To concluded, cluster analysis identified three statistically-driven groups among AF patients treated with CA with different risks for arrhythmia recurrences.

AFA-Recur: an ESC EORP AFA-LT registry machine-learning web calculator predicting atrial fibrillation recurrence after ablation

AIMS

Atrial fibrillation (AF) recurrence during the first year after catheter ablation remains common. Patient-specific prediction of arrhythmic recurrence would improve patient selection, and, potentially, avoid futile interventions. Available prediction algorithms, however, achieve unsatisfactory performance. Aim of the present study was to derive from ESC-EHRA Atrial Fibrillation Ablation Long-Term Registry (AFA-LT) a machine-learning scoring system based on pre-procedural, easily accessible clinical variables to predict the probability of 1-year arrhythmic recurrence after catheter ablation.

METHODS AND RESULTS

Patients were randomly split into a training (80%) and a testing cohort (20%). Four different supervised machine-learning models (decision tree, random forest, AdaBoost, and k-nearest neighbour) were developed on the training cohort and hyperparameters were tuned using 10-fold cross validation. The model with the best discriminative performance on the testing cohort (area under the curve-AUC) was selected and underwent further optimization, including re-calibration. A total of 3128 patients were included. The random forest model showed the best performance on the testing cohort; a 19-variable version achieved good discriminative performance [AUC 0.721, 95% confidence interval (CI) 0.680-0.764], outperforming existing scores (e.g. APPLE score: AUC 0.557, 95% CI 0.506-0.607). Platt scaling was used to calibrate the model. The final calibrated model was implemented in a web calculator, freely available at http://afarec.hpc4ai.unito.it/.

CONCLUSION

AFA-Recur, a machine-learning-based probability score predicting 1-year risk of recurrent atrial arrhythmia after AF ablation, achieved good predictive performance, significantly better than currently available tools. The calculator, freely available online, allows patient-specific predictions, favouring tailored therapeutic approaches for the individual patient.

Clinical relevance of the blanking period on late recurrence after catheter ablation of atrial fibrillation

INTRODUCTION

Recurrence of atrial fibrillation (AF) within the blanking period after catheter ablation (CA) is traditionally classified as a transient and benign event. However, recent findings suggest that early recurrence (ER) is associated with late recurrence (LR), challenging the predefined "blanking period". We aimed to determine the clinical and procedural predictors of ER and LR after CA and establish the risk of LR in patients who experience ER.

METHODS AND RESULTS

Retrospective single-centre study including all patients who underwent a first procedure of AF CA between 2017 and 2019. ER was defined as any recurrence of AF, atrial flutter or atrial tachycardia >30 s within 90 days after CA and LR as any recurrence after 90 days of CA. A total of 399 patients were included, 37% women, median age of 58 years [49-66] and 77% had paroxysmal AF. Median follow-up was 33 months (from 13 to 61). ER after CA was present in 14% of the patients, and LR was reported in 32%. Among patients who experienced ER, 84% also had LR (p < .001). Patients with ER had a higher prevalence of moderate/severe valvular heart disease, persistent AF, previous electrical cardioversion, a larger left atrium, higher coronary artery calcium score, and higher rates of intraprocedural electrical cardioversion and cardiac fibrosis on eletroanatomical mapping compared with patients without ER. After covariate adjustment, ER and female sex were defined as independent predictors of LR (hazard ratio [HR] 4.69; 95% confidence interval [CI], 2.99-7.35; p < .001 and HR 2.73; 95% CI, 1.47-5.10; p = .002, respectively).

CONCLUSION

The risk of LR after an index procedure of CA was significantly higher in patients with ER (five-fold increased risk). These results support the imperative need to clarify the clinical role of the blanking period.

10-Year Outcomes of Patients With Non-Paroxysmal Atrial Fibrillation Undergoing Catheter Ablation

BACKGROUND

Radiofrequency catheter ablation (RFCA) is commonly performed in patients with non-paroxysmal atrial fibrillation (AF), but because very long-term follow-up results of RFCA are limited, we investigated the 10-year RFCA outcomes of non-paroxysmal AF.

METHODS AND RESULTS

We retrospectively enrolled 100 patients (89 men, mean age 53.5±8.4years) with drug-refractory symptomatic non-paroxysmal AF who underwent 3D electroanatomic-guided RFCA. Procedural characteristics at index procedures and clinical outcomes were investigated. In the index procedures, all patients had pulmonary vein isolation, 56 (56.0%), 48 (48.0%), and 32 (32.0%) underwent additional linear, complex fractionated atrial electrogram (CFAE) and non-pulmonary vein (NPV) foci ablations, respectively. After 124.1±31.7 months, 16 (16%) patients remained in sinus rhythm after just 1 procedure (3 with antiarrhythmic drugs [AAD]) and after multiple (2.1±1.3) procedures in 53 (53.0%) patients (22 with AAD). Left atrial (LA) diameter (hazard ratio HR 1.061; 95% confidence interval (CI) 1.020 to 1.103; P=0.003), presence of NPV triggers (HR 1.634; 95% CI 1.019 to 2.623; P=0.042) and undergoing CFAE ablation (HR 2.003; 95% CI 1.262 to 3.180; P=0.003) in the index procedure were independent predictors for recurrent atrial tachyarrhythmia.

CONCLUSIONS

The 10-year outcomes of single RFCA in non-paroxysmal AF were unsatisfactory. Enlarged LA, presence of NPV triggers, and undergoing CFAE ablation in the index procedure independently predicted single-procedure recurrence. Multiple procedures are required to achieve adequate rhythm control.

Association of Uric Acid Albumin Ratio with Recurrence of Atrial Fibrillation after Cryoballoon Catheter Ablation

Objective: Despite improvements in the technology of catheter ablation of atrial fibrillation (AF), recurrences are still a major problem, even after a successful procedure. The uric acid/albumin ratio (UAR), which is an inexpensive and simple laboratory parameter, has recently been introduced in the literature as a predictor of adverse cardiovascular events. Hence, we aimed to investigate the relationship between the UAR and AF recurrence after catheter ablation. Methods: A total of 170 patients who underwent successful catheter ablation for AF were included. The primary outcome was the late recurrence after treatment. The recurrence (+) and recurrence (−) groups were compared for clinical, laboratory and procedural characteristics as well as the predictors of recurrence assessed by regression analysis. Results: In our study population, 53 (26%) patients developed AF recurrence after catheter ablation. Mean UAR was higher in the recurrence (+) group compared to recurrence (−) group (2.4 ± 0.9 vs. 1.8 ± 0.7, p < 0.01). In multivariable regression analysis, left atrial diameter (HR: 1.08, 95% CI: 1.01−1.16, p = 0.01) and UAR (HR:1.36, 95% CI: 1.06−1.75, p = 0.01) were found to be independent predictors of recurrence. In ROC analysis, the UAR > 1.67 predicted recurrence with a sensitivity of 77% and a specificity of 57% (AUC 0.68, p < 0.01). Conclusion: For the first time in the literature, the UAR were found to be correlated independently with AF recurrence after catheter ablation.

Validation of seven risk scores in an independent cohort: the challenge of predicting recurrence after atrial fibrillation ablation

Purpose

Several predictive scores for atrial fibrillation (AF) recurrence after AF ablation have been developed. We compared the predictive value of seven previously described risk scores ((CHADS2 and CHA2DS2-VASC, HATCH, APPLE, CAAP-AF, BASE-AF2, MB-LATER) for prediction of AF recurrence risk at 12 months after AF ablation in our patient cohort. Further, we aimed to identify additional variables to predict recurrences after AF ablation.

Methods

We used data from our digital AF ablation registry to compare the previously published scores in an independent cohort (n = 883, 50.8% with paroxysmal AF). The scores were chosen based on earlier publications and availability of relevant data.

Results

The BASE-AF2 (AUC 0.630, p < 0.001), MB-LATER (AUC 0.612, p < 0.001), CAAP-AF (AUC 0.591, p < 0.001), APPLE (AUC 0.591, p < 0.001) and CHA2DS2-VASC (AUC 0.547, p = 0.018) scores had a statistically significant but modest predictive value for 12-month AF recurrence. None of the scores were significantly superior. Other analyzed scores had no predictive value. There was no difference in the predictive value for 12-month recurrence of AF between first procedure vs. redo procedure and RF ablation vs. cryoablation. Unlike other scores, MB-LATER showed better predictive value for paroxysmal vs. persistent AF (AUC 0.632 vs. 0.551, p = 0.038). In the multivariate logistic regression, only age (p = 0.006), number of prior electrical cardioversions (p < 0.001) and early AF recurrence (p < 0.001) were independent predictors of AF recurrence.

Conclusion

Despite numerous available scores, predicting recurrences after AF ablation remains challenging. New predictors are needed, potentially based on interventions, as well as novel genetic, functional and anatomic parameters.

Development and validation of a novel risk model for predicting atrial fibrillation recurrence risk among paroxysmal atrial fibrillation patients after the first catheter ablation

AIMS

Several models have been developed to predict the risk of atrial fibrillation (AF) recurrence after radiofrequency catheter ablation (RFCA). However, these models are of poor quality from the start. We, therefore, aimed to develop and validate a predictive model for post-operative recurrence of AF.

MATERIALS AND METHODS

In a study including 433 patients undergoing the first circumferential pulmonary vein isolation (CPVI) procedure, independent predictors of AF recurrence were retrospectively identified. Using the Cox regression of designated variables, a risk model was developed in a random sample of 70% of the patients (development cohort) and validated in the remaining (validation cohort) 30%. The accuracy and discriminative power of the predictive models were evaluated in both cohorts.

RESULTS

During the established 12 months follow-up, 134 patients (31%) recurred. Six variables were identified in the model including age, coronary artery disease (CAD), heart failure (HF), hypertension, transient ischemic attack (TIA) or cerebrovascular accident (CVA), and left atrial diameter (LAD). The model showed good discriminative power in the development cohort, with an AUC of 0.77 (95% confidence interval [CI], 0.69-0.86). Furthermore, the model shows good agreement between actual and predicted probabilities in the calibration curve. The above results were confirmed in the validation cohort. Meanwhile, decision curve analysis (DCA) for this model also demonstrates the advantages of clinical application.

CONCLUSION

A simple risk model to predict AF recurrence after ablation was developed and validated, showing good discriminative power and calibration.

CHA2DS2VASc score as a predictor of ablation success defined by continuous long-term monitoring

BACKGROUND

There are few reliable risk stratification tools for successful atrial fibrillation catheter ablation (AFCA) and most prior studies have used short-term external monitors to define success. CHA₂DS₂VASc score may be useful in predicting AF recurrence. We investigated whether CHA₂DS₂VASc score correlates with AFCA success as measured by continuous monitoring via cardiac implantable electronic devices (CIEDs).

METHODS

Using the Optum® de-identified Electronic Health Record dataset (01/2007 to 06/2019) linked with the Medtronic CareLink™ database, we identified patients who underwent a 1st AFCA procedure following CIED implantation. Success was defined as absence of ≥ 1 h of AF following a 3-month blanking period.

RESULTS

A total of 632 patients (age 67 ± 9.1 years, 73.3% male, CHA₂DS₂VASc 3.6 ± 1.8, 36.9% paroxysmal AF) were analyzed and included 35.1% insertable cardiac monitor, 28.8% PPM, 21.4% ICD, 13.6% CRT-D, and 1.1% CRT-P. Success at 24 months post blanking period was 40.3% (95% CI 32.6-49.7%), 36.2% (95% CI 26.9-45.4%), and 21.8% (95% CI 14.6-32.5%) for CHA₂DS₂VASc subgroups of 0-2, 3-4, and ≥ 5, respectively. Median daily burden of AF was reduced to zero regardless of CHA₂DS₂VASc score, but there were significant differences in survival free from any AF ≥ 1 h between the three CHA₂DS₂VASc subgroups (p = 0.013). Patients with a score ≥ 5 had a HR of 1.29 (95% CI 1.00-1.67) for AF recurrence compared to patients with a score of 0-2, with similar results after controlling for AF type.

CONCLUSIONS

In real-world patients with continuous monitoring undergoing AFCA, only CHA₂DS₂VASc scores ≥ 5 predicted higher AF recurrence.

P-wave duration and atrial fibrillation recurrence after catheter ablation: a systematic review and meta-analysis

AIMS

Atrial fibrillation (AF) is a global health problem with high morbidity and mortality. Catheter ablation (CA) can reduce AF burden and symptoms, but AF recurrence (AFr) remains an issue. Simple AFr predictors like P-wave duration (PWD) could help improve AF therapy. This updated meta-analysis reviews the increasing evidence for the association of AFr with PWD and offers practical implications.

METHODS AND RESULTS

Publication databases were systematically searched and cohort studies reporting PWD and/or morphology at baseline and AFr after CA were included. Advanced interatrial block (aIAB) was defined as PWD ≥ 120 ms and biphasic morphology in inferior leads. Random-effects analysis was performed using the Review Manager 5.3 and R programs after study selection, quality assessment, and data extraction, to report odds ratio (OR) and confidence intervals. : Among 4175 patients in 22 studies, 1138 (27%) experienced AFr. Patients with AFr had longer PWD with a mean pooled difference of 7.8 ms (19 studies, P < 0.001). Pooled OR was 2.04 (1.16-3.58) for PWD > 120 ms (13 studies, P = 0.01), 2.42 (1.12-5.21) for PWD > 140 ms (2 studies, P = 0.02), 3.97 (1.79-8.85) for aIAB (5 studies, P < 0.001), and 10.89 (4.53-26.15) for PWD > 150 ms (4 studies, P < 0.001). There was significant heterogeneity but no publication bias detected.

CONCLUSION

P-wave duration is an independent predictor for AF recurrence after left atrium ablation. The AFr risk is increasing exponentially with PWD prolongation. This could facilitate risk stratification by identifying high-risk patients (aIAB, PWD > 150 ms) and adjusting follow up or interventions.

Preoperative Prediction of Catheter Ablation Outcome in Persistent Atrial Fibrillation Patients through Spectral Organization Analysis of the Surface Fibrillatory Waves

Catheter ablation (CA) is a commonly used treatment for persistent atrial fibrillation (AF). Since its medium/long-term success rate remains limited, preoperative prediction of its outcome is gaining clinical interest to optimally select candidates for the procedure. Among predictors based on the surface electrocardiogram, the dominant frequency (DF) and harmonic exponential decay (γ) of the fibrillatory waves (f-waves) have reported promising but clinically insufficient results. Hence, the main goal of this work was to conduct a broader analysis of the f-wave harmonic spectral structure to improve CA outcome prediction through several entropy-based measures computed on different frequency bands. On a database of 151 persistent AF patients under radio-frequency CA and a follow-up of 9 months, the newly introduced parameters discriminated between patients who relapsed to AF and those who maintained SR at about 70%, which was statistically superior to the DF and approximately similar to γ. They also provided complementary information to γ through different combinations in multivariate models based on lineal discriminant analysis and report classification performance improvement of about 5%. These results suggest that the presence of larger harmonics and a proportionally smaller DF peak is associated with a decreased probability of AF recurrence after CA.

Effect of Bi-Atrial Size and Function in Patients With Paroxysmal or Permanent Atrial Fibrillation

Atrial fibrillation (AF) remains the most common arrhythmia in clinical practice. The choice between a rate-control and rhythm-control strategy depends on various factors, including the anatomical and functional substrate. This study investigates the anatomical and functional characteristics of both atria in patients with AF and explores the potential therapeutic implications. From an ongoing registry of patients with paroxysmal or permanent AF, those who underwent cardiac computed tomography (CCT) were included. Left atrial (LA) and right atrial (RA) sizes were measured on CCT, whereas bi-atrial function was quantified with speckle tracking strain echocardiography. The mean LA volume index was 41.6 ± 5.6 ml/m², and the mean RA volume index was 71.0 ± 21.6 ml/m². Mean LA reservoir strain was 24.3 ± 15.1%, compared with the mean RA reservoir strain of 21.6 ± 13.2%. Patients with smaller LA volumes had higher LA reservoir strain values than those with larger LA volumes (24.6% [interquartile range (IQR) 15.8 to 35.8] vs 16.5% [IQR 11.2 to 25.0], p <0.001). Patients with permanent AF had larger LA volumes (44.0 [IQR 33.7 to 55.2] ml/m² vs 36.9 [IQR 30.1 to 47.1] ml/m², p = 0.025) compared with paroxysmal AF. Patients with permanent AF had more impaired LA reservoir strain (15.5% [IQR 11.6 to 22.7] vs 26.9% [IQR 17.4 to 35.6], p <0.001) compared with paroxysmal AF. Similar trends were observed in the RA. In conclusion, atrial substrate characterization by CCT and speckle tracking strain echocardiography may have therapeutic implications, especially for choosing between a rate-control and rhythm-control strategy.

Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation in Patients with Atrial Fibrillation

Current guidelines on atrial fibrillation (AF) emphasized that radiofrequency catheter ablation (RFCA) should be decided after fully considering its prognosis. However, a robust prediction model reflecting the complex interactions between the features affecting prognosis remains to be developed. In this paper, we propose a deep learning model for predicting the late recurrence after RFCA in patients with AF. Aiming to predict the late recurrence (LR) of AF within 1 year after pulmonary vein isolation, we designed a multimodal model based on the multilayer perceptron architecture. For quantitative evaluation, we conducted 4-fold cross-validation on data from 177 AF patients including 47 LR patients. The proposed model (area under the receiver operating characteristic curve-AUROC, 0.766) outperformed the acute patient physiologic and laboratory evaluation (APPLE) score (AUROC, 0.605), CHA2DS2-VASc score (AUROC, 0.595), linear regression (AUROC, 0.541), logistic regression (AUROC, 0.546), extreme gradient boosting (AUROC, 0.608), and support vector machine (AUROC, 0.638). The proposed model exhibited better performance than clinical indicators (APPLE and CHA2DS2-VASc score) and machine learning techniques (linear regression, logistic regression, extreme gradient boosting, and support vector machine). The model will support clinical decision-making for selecting good responders to the RFCA intervention.

Current Understanding of Atrial Fibrillation Recurrence After Atrial Fibrillation Ablation: From Pulmonary Vein to Epicardium

Recurrence of atrial fibrillation (AF) after catheter ablation is common, with pulmonary vein (PV) reconnection considered the most likely cause. However, technologies such as contact force-sensing, irrigated catheters, and ablation index (AI)-guided ablation strategies have resulted in more durable PV isolation. As a result, it is difficult to predict which patients will develop AF recurrence despite durable PV isolation, with evolving non-PV atrial substrates thought to be a key contributor to late recurrences. Deciphering the complex mechanisms of AF recurrence beyond the cornerstone of PV isolation therefore remains challenging. Recently, there have been several important advances that may lead to better understanding and treatment of this challenging clinical entity: percutaneous epicardial access and mapping, late gadolinium enhancement magnetic resonance imaging (LGE-MRI), improvements in high-resolution electroanatomic mapping, and new ablation energy sources, specifically pulsed-field ablation. This review aims to synthesize the current literature in an effort to better understand arrhythmia mechanisms and treatment targets in patients with AF/Atrial tachycardia (AT) recurrence post-ablation. This article is protected by copyright. All rights reserved.