Catheter Ablation for Persistent Atrial Fibrillation

From Paroxysmal to Persistent Atrial Fibrillation: Progressive Fibrosis of the Left Atrial Posterior Wall

BACKGROUND

The path from paroxysmal to persistent atrial fibrillation (AF) is still poorly understood, leading to suboptimal treatment outcomes.

OBJECTIVES

In this study, the authors sought to investigate the level of fibrosis in different stages of AF with the use of 18F-labeled aluminum fluoride (AlF) targeting fibroblast activation protein inhibitor (FAPI) positron emission tomography (PET)-magnetic resonance imaging (MRI).

METHODS

A total of 78 patients with AF and 49 health volunteers were enrolled in this study. All participants received FAPI-PET-MRI. Measurement of positive ratios and the proportion was performed in various regions of the left atrium posterior wall (LAPW), the atrial septum, anterior wall, appendage, and roof. Patients were categorized into paroxysmal (PAF), persistent (PsAF), and permanent (PmAF) AF groups based on 7-day ambulatory monitoring and history. Another cohort of 36 patients undergoing cardiac surgery, with 124 fragments of image-guided tissue, consented to biopsy during cardiac surgery for histology examinations.

RESULTS

The positive ratio for fibrosis was significantly higher in the PsAF and PmAF groups compared with the PAF and healthy volunteer groups across all atrial regions (P < 0.05). The LAPW showed the highest level of fibrosis. The AUC for the positive ratio was 0.991 to differentiate PAF from PsAF in the LA (cutoff: 0.072), and 0.983 in the LAPW (cutoff: 0.025). Between PsAF and PmAF, the AUC was 0.756 in the LA (cutoff: 0.382). Histologic analysis demonstrated an increased area of fibrotic deposition in regions with increased 18F-FAPI uptake.

CONCLUSIONS

LAPW fibrosis may be an important factor in the progression from PAF to PsAF. (A Single-Center, Prospective, Cohort Study on the Clinical Application of 18F-FAPI PET Imaging in Atrial Fibrillation; ChiCTR2300075806).

Incidence of silent cerebral events detected by MRI in patients with atrial fibrillation undergoing pulsed field ablation vs thermal ablation: A systematic review and network meta-analysis

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and catheter ablation has been demonstrated to achieve superior success rates compared with antiarrhythmic drugs. However, this procedure entails certain risks, including silent cerebral events (SCEs), which may affect cognitive function. This network meta-analysis aimed to determine the global incidence of SCEs in patients with AF undergoing catheter ablation and to compare the incidence across energy sources and catheter types. Our analysis included 86 trials involving 10,456 patients with AF, with a pooled SCE incidence of 19.1%. For pulsed field ablation, the incidence of SCEs was 14.4%; thermal ablation techniques showed rates of 17.7% for radiofrequency ablation, 20.8% for cryoballoon ablation, and 32.7% for laser ablation. No significant differences were found between pulsed field ablation and thermal ablation in SCE incidence. The comparison of SCE incidence between different catheter types revealed variations. The HD Mesh Ablator demonstrated the lowest incidence rate (15.1%), whereas the PVAC catheter had the highest (36.2%). The Farawave catheter had an incidence rate of 18.5% and showed no significant differences compared with most thermal catheters, except for the HD Mesh Ablator (relative risk, 0.15; 95% credible interval, 0.03-0.89). Our findings indicate that a substantial proportion of patients experience SCEs after catheter ablation for AF, with an overall incidence of approximately 19.1% occurring within 1 week (mostly within 72 hours) after ablation. No significant differences were observed in SCE incidence between pulsed field ablation and thermal ablation or between the Farawave catheter and most thermal catheters.

Development and validation of a predictive model for atrial fibrillation recurrence post-catheter ablation in patients with nonvalvular atrial fibrillation on the basis of hemodynamic parameters

BACKGROUND

The influence of hemodynamic parameters on the recurrence of atrial fibrillation (AF) after catheter ablation is not well known, and it remains unclear whether a nomogram combining risk factors and hemodynamic parameters improves prediction accuracy.

OBJECTIVE

This study aimed to develop a nomogram on the basis of echocardiographic hemodynamic parameters for predicting AF recurrence after catheter ablation in nonvalvular atrial fibrillation (NVAF).

METHODS

A total of 380 consecutive patients with NVAF undergoing AF catheter ablation treatment were prospectively included. Patients were divided into training and validation cohorts in a 7:3 ratio. The follow-up time averaged 9 months with a median of 12 months, during which 132 patients (34.7%) experienced AF recurrence.

RESULTS

Least absolute shrinkage and selection operator regression and Cox regression analyses identified 4 significant predictors of AF recurrence: persistent AF (hazard ratio [HR] 1.63; 95% confidence interval [CI] 1.02-2.61; P = .041), S/D ratio of pulmonary vein (HR 0.50; 95% CI 0.30-0.84; P = .009), left atrial acceleration factor α (HR 1.31; 95% CI 1.02-1.68; P = .032), and left atrial appendage peak emptying flow velocity (HR 0.98; 95% CI 0.97-0.99; P = .004). On the basis of these 4 variables, a predictive nomogram was constructed. The nomogram demonstrated C indices of 0.664 and 0.728 for predicting 1- and 2-year AF recurrence, respectively, in the validation cohort. The Kaplan-Meier survival analysis indicated that a Nomo score of >128 was associated with a higher risk of AF recurrence.

CONCLUSION

Hemodynamic parameters may offer valuable insight into predicting AF recurrence after catheter ablation. Our study successfully developed a reliable nomogram on the basis of echocardiographic hemodynamic parameters to estimate the risk of AF recurrence after catheter ablation in patients with NVAF.

Epigallocatechin-3-Gallate Inhibits Atrial Fibrosis and Reduces the Occurrence and Maintenance of Atrial Fibrillation and its Possible Mechanisms

BACKGROUND

Atrial fibrosis is one of the main causes of the onset and recurrence of atrial fibrillation (AF), for which there is no effective treatment. The aim of this study was to investigate the effect and mechanism of epigallocatechin-3-gallate (EGCG) on AF in rats.

METHODS

The rat model of AF was established by rapid pacing induction after angiotensin-II (Ang-II) induced atrial fibrosis to verify the relationship between atrial fibrosis and the AF. The expression levels of TGF-β/Smad3 pathway molecules and lysyl oxidase (LOX) in AF were detected. Subsequently, EGCG was used to intervene Ang-II-induced atrial fibrosis to explore the role of EGCG in the treatment of AF and its inhibitory mechanism on fibrosis. It was further verified that EGCG inhibited the production of collagen and the expression of LOX through the TGF-β/Smad3 pathway at the cellular level.

RESULTS

The results showed that the induction rate and maintenance time of AF in rats increased with the increase of the degree of atrial fibrosis. Meanwhile, the expressions of Col I, Col III, molecules related to TGF-β/Smad3 pathway, and LOX increased significantly in the atrial tissues of rats in the Ang-II induced group. EGCG could reduce the occurrence and maintenance time of AF by inhibiting the degree of Ang-induced rat atrial fibrosis. Cell experiments confirmed that EGCG could reduce the synthesis of collagen and the expression of LOX in cardiac fibroblast induced by Ang-II. The possible mechanism is to down-regulate the expression of genes and proteins related to the TGF-β/Smad3 pathway.

CONCLUSION

EGCG could downregulate the expression levels of collagen and LOX by inhibiting the TGF-β/Smad3 signaling pathway, alleviating Ang-II-induced atrial fibrosis, which in turn inhibited the occurrence and curtailed the duration of 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.

Non-insulin-based insulin resistance indexes in predicting atrial fibrillation recurrence following ablation: a retrospective study

BACKGROUND

Insulin resistance (IR) is involved in the pathophysiological processes of arrhythmias. Increasing evidence suggests triglyceride and glucose (TyG) index, metabolic score for insulin resistance (METS-IR), triglyceride glucose-body mass index (TyG-BMI), and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio are simple and reliable surrogates for IR. Although they have been associated with atrial fibrillation (AF), evidence supporting this is limited. Here, this is the first study to investigate the association between TyG-BMI index and AF recurrence following radiofrequency catheter ablation (RFCA). The performance of the four non-insulin-based IR indexes in predicting AF recurrence after ablation was explored.

METHODS

A total of 2242 AF patients who underwent a de novo RFCA between June 2018 to January 2022 at two hospitals in China were included in this retrospective study. The predictive values of IR indexes for AF recurrence after ablation were assessed.

RESULTS

During 1-year follow-up, 31.7% of patients experienced AF recurrence. The multivariable analysis revealed that TyG index, METS-IR, and TyG-BMI index were independent risk factors for AF recurrence. Restricted cubic spline analysis revealed a connection between METS-IR, TyG-BMI index, and AF recurrence (P < 0.001). Furthermore, incorporating the METS-IR or TyG-BMI index to the basic risk model with fully adjusted factors considerably enhanced the forecast of AF recurrence, as demonstrated by the C-statistic, continuous net reclassification improvement, and integrated discrimination improvement.

CONCLUSIONS

TyG index, METS-IR, and TyG-BMI index were independently associated with AF recurrence following ablation. Among the four non-insulin-based IR indexes, TyG-BMI had the highest predictive value, followed by METS-IR.