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Review

Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A State-of-the-Art Review

by
Roopeessh Vempati
1,
Ayushi Garg
2,
Maitri Shah
3,
Nihar Jena
4,
Kavin Raj
5,
Yeruva Madhu Reddy
6,
Amit Noheria
6,
Quang Dat Ha
1,
Dinakaran Umashankar
1 and
Christian Toquica Gahona
7,*
1
Department of Internal Medicine, Trinity Health Oakland Hospital, Pontiac, MI 48341, USA
2
Department of Internal Medicine, Trident Medical Center, Charleston, SC 29406, USA
3
Department of Internal Medicine, University of Michigan Health Sparrow, Lansing, MI 48912, USA
4
Interventional Cardiology Division, Department of Cardiology, Marshall University, Huntington, WV 25755, USA
5
Department of Cardiology, University of California Riverside, Riverside, CA 92521, USA
6
Electrophysiology Division, Department of Cardiology, Kansas University Medical Center, Kansas City, KS 66160, USA
7
Department of Cardiology, Trinity Health Oakland Hospital, Pontiac, MI 48341, USA
*
Author to whom correspondence should be addressed.
Hearts 2025, 6(2), 12; https://doi.org/10.3390/hearts6020012
Submission received: 3 March 2025 / Revised: 12 April 2025 / Accepted: 22 April 2025 / Published: 24 April 2025

Abstract

:
Catheter ablation (CA) was found to outperform antiarrhythmic drug therapy (AAD), and it is a key treatment for rhythm control for patients with symptomatic atrial fibrillation (AF). Nevertheless, the procedure’s effectiveness is limited by recurrence rates. Identifying determinants of effective ablation is critical for optimizing patient selection, operative results, and long-term rhythm management strategies. In this state-of-the-art review, we have comprehensively discussed the various factors that can determine the recurrence of AF after a successful CA.

1. Introduction

Atrial fibrillation (AF) is the arrhythmia most frequently encountered, having the highest prevalence [1]. The global burden of AF has been rising consistently over the past three decades and is vastly influenced by prolonged lifespans and changes in lifestyle [2]. In the United States (US), the prevalence of AF was estimated to be 5.2 million in the year 2010, and it is anticipated that it will reach 12.1 million by the year 2030. Correspondingly, estimates for US incidence were 1.2 million cases in 2010, with an expectation to rise to 2.6 million cases by 2030 [3]. With the increase in common cardiometabolic risk factors including advancing age, sedentary lifestyle, obesity, hypertension (HTN), type 2 diabetes mellitus (T2DM), established cardiovascular disease (CVD), obstructive sleep apnea (OSA), and chronic kidney disease (CKD), the AF trend is expected to be on the rise [3].
Catheter ablation (CA) is a frequently employed therapeutic intervention for managing patients with AF, particularly in those whose symptoms are resistant to antiarrhythmic medication [4]. The evidence to support CA procedures is steadily increasing, with multiple randomized controlled trials (RCTs) and large registries showing improvement in clinical outcomes [3]. The data indicate that CA is superior to antiarrhythmic medications in managing both persistent and paroxysmal AF, and the timely application of rhythm control strategies significantly enhances the success rates of AF ablation [3,5,6]. In this review, we will discuss the most updated determinant factors of AF recurrence after CA.
Definitions of successful CA and AF recurrence can vary across studies and clinical guidelines. Some authors consider CA successful simply if the burden of AF is reduced. Others define success as improvement in symptoms, even if AF is not eliminated [7]. According to the 2024 EHRA/HRS/APHRS/LAHRS Expert Consensus Statement, success after catheter ablation for AF is defined as being free from atrial arrhythmias—including AF, atrial flutter (AFL), or atrial tachycardia (AT)—for more than 30 s following a single ablation procedure. This success is assessed over a minimum follow-up period of 12 months. The consensus also recommends reporting outcomes both when patients are off and on antiarrhythmic drugs (AADs) to ensure clarity and consistency across studies [8].
AF recurrence has remained a significant challenge despite the introduction of new devices and the advancement of CA techniques. The “blanking period” refers to the initial phase following the procedure, during which early recurrences are not viewed as indicative of long-term ablation failure. This is because temporary arrhythmias may occur as part of the heart’s healing process [9]. In a predefined sub-study of the CIRCA-DOSE trial, it was found that early recurrence (more than 52 days of CA) can predict the later recurrence of AF with 95% specificity [10]. A significant update in the 2024 document is the revision of the blanking period, which has been shortened from the traditional 3 months [11] to 8 weeks. Any atrial arrhythmia lasting more than 30 s during these 8 weeks is classified as an early recurrence; arrhythmias that occur after this period, up to 12 months post-ablation, are classified as late recurrences [8]. Recurrences of AF can be influenced by various factors, such as the presence of underlying heart disease and the duration of time the patient has been in AF [12]. Early recurrences of arrhythmia can be attributed to several mechanisms, including short-term inflammatory processes, myocardial edema, oxidative stress, transient changes in autonomic function, and incomplete isolation of the pulmonary veins (PVs). These factors are often reversible and do not necessarily indicate long-term failure. In contrast, late recurrences are more frequently linked to structural remodeling, which involves fibrosis, scar maturation, and triggers that originate outside the PVs, and these late recurrences are typically progressive and are less likely to resolve on their own [8]. Many patients can achieve long-term success following AF ablation procedures, which is defined as remaining free from arrhythmia recurrence for at least 36 months without the use of antiarrhythmic therapy [13,14]. It is important to study the predictors of AF recurrence after a successful CA to optimize patient outcomes. In this review, we aim to comprehensively discuss various predictors of AF recurrence after successful CA, which have been published in the literature.

2. Predictors of Atrial Fibrillation Recurrence

Several risk factors have been depicted to have a correlation with AF recurrence post-CA (Figure 1 and Figure 2). The following classification is an attempt to arrange such clinical and procedural factors related to recurrence.

2.1. Non-Modifiable Clinical Factors

2.1.1. Age

Age has been proven to be an independent predictor of AF recurrence in numerous trials that studied both non-surgical as well as surgical ablation techniques [15,16,17,18,19]. According to the study by Bunch et al., patients over 70 years of age have noticeably higher rates of AF recurrence, indicating that age has a significant impact on post-ablation outcomes [17]. The results can be attributed to the structural and functional changes induced by aging in the atria, including dilatation, reduced regional conduction velocity, extended atrial effective refractory periods, left atrial fibrosis, and compromised sinus node functionality. Additionally, the presence of age-related health conditions significantly raises the risk of recurrence [15,20].

2.1.2. Gender

Compared to men, women typically have lower success rates after catheter ablation for AF [21,22]. This is because women are more likely to have long-standing, persistent AF, have more severe symptoms, have more non-PV triggers, and have AF present at older ages [23,24,25]. Additionally, atria, particularly those surrounding the PVs, frequently exhibit greater scarring (fibrosis) in women with persistent AF, which may lessen the efficacy of ablation [25]. Depending on the type of AF, sex has varying effects on ablation results. After radiofrequency ablation (RFA), women with persistent AF experience higher rates of recurrence, whereas men and women experience comparable rates of AF recurrence among those with paroxysmal AF [26,27]. Variations in the structure of the heart, hormonal effects, electrical activity, and alterations in the atria between men and women may account for these discrepancies [25,28,29].

2.1.3. Genetics

An emerging field called ablatogenomics has the potential to direct AF ablation strategies by forecasting thromboembolic risk, CA success, and cardioversion success [30]. Numerous investigations have discovered genetic variations on chromosomes 4q25 and 16q22 that predict an increased risk of AF development and are potential markers for CA therapy. However, other researchers did not clearly detect a connection between recurrence and genetic susceptibility [31,32,33,34,35]. There was no discernible genetic vulnerability to recurrence following ablation, according to Shoemaker et al. Despite the fact that 75% of the susceptibility alleles were linked to a higher risk of recurrence, 25% showed a lower risk [34]. The net genetic effect may be reduced by the combined effect. These results suggest that the link between genetic predisposition and AF recurrence may not be as simple as it seems. AF recurrence seems conditional on other variables, namely the CA procedure characteristics and individual risk factors that are unique to each patient [34]. In addition, genetic susceptibility may influence atrial remodeling through ion channel dysfunction and fibrotic signaling (TGF-β1), which can lead to recurrence [36].

2.2. Modifiable Clinical Factors

2.2.1. Hypertension

The risk of AF is significantly escalated by causing changes in the atria, such as increased wall thickness, fibrosis, and dilation. The activation of the renin–angiotensin–aldosterone system (RAAS) in hypertensive patients further contributes to these harmful effects [8,37]. In a study conducted by Santoro et al. involving 531 consecutive patients, the risk of recurrence was found to be 40.6% for those with uncontrolled hypertension, 28.1% for those with controlled HTN, and 25.7% for patients without HTN. Comparable rates of AF recurrence among patients without HTN and those with well-controlled HTN highlight the importance of intensive blood pressure (BP) control [38]. In contrast, research based on the German ablation registry revealed that, when compared to normotensive patients, those with HTN are not at risk of AF recurrence [39]. SMAC-AF (Substrate Modification with Aggressive BP Control) investigated how the recurrence of AF is determined by the BP control before the procedure, wherein the study participants (n = 184) were randomly assigned to aggressive (<120/80 mmHg) or standard BP control (<140/80 mmHg). After a follow-up of 14 months, comparable rates of arrhythmia recurrence were found between the two groups (61.4% vs. 61.2%, respectively). It is possible that the true impact of BP control might have been undermined in this study, as both groups lowered their BP below their baseline levels after the follow-up period [40]. Despite these contradictory findings, guidelines emphasized the importance of managing various risk factors comprehensively [8,11]. The ARREST-AF study demonstrated that treating modest HTN on its own has not been beneficial. However, higher rates of sinus rhythm maintenance were found when comprehensive risk factor management was applied among overweight or obese individuals [41].

2.2.2. Type 2 Diabetes Mellitus

T2DM was found to be an independent predictor of AF recurrence after CA procedures [42]. Inflammation, fibrosis, and structural and electrical atrial remodeling that occur in T2DM patients play a role in the pathophysiology [42]. The risk of an early recurrence post-CA was linked to newly diagnosed T2DM [42]. While some studies have found no discernible difference in AF recurrence following CA between the T2DM and non-T2DM groups [43,44,45], a number of studies have noted an increase, particularly in PAF (paroxysmal AF) patients with T2DM [46,47]. Advanced age, high body mass index (BMI), and elevated basal glycated hemoglobin levels are associated with increased rates of AF recurrence. This suggests that metabolic changes related to DM may contribute to further episodes of arrhythmia [43].

2.2.3. Obesity

According to Liu et al., patients with a BMI greater than 28 had a significantly higher chance of experiencing an AF recurrence [48]. Obesity facilitates AF recurrence following CA through the promotion of both structural and electrical remodeling of the atria. It increases susceptibility to AF triggers by decreasing the PVs’ effective refractory periods [49]. Additionally, oxidative stress, hemodynamic alterations, and chronic low-grade inflammation are linked to obesity, all of which contribute to a proarrhythmic environment [49]. The effects of electroanatomical changes in atrial myocardial cells, especially in patients with DM, are magnified by the presence of obesity, which is a key indicator of metabolic syndrome. This influence appears to be more significant than the duration of AF, whether it is paroxysmal or persistent. Further studies are needed to refine risk assessment and optimize treatment strategies for this population [43]. Weight management is a key factor in the prevention of AF in patients at a high risk of recurrence [49].

2.2.4. Epicardial Adipose Tissue

There is substantial evidence linking epicardial adipose tissue (EAT) to AF and post-CA AF recurrence [50]. EAT constitutes ganglionated plexuses and adipocytes, and it acts as an active organ, having direct contact with the myocardium [51]. EAT can secrete interleukin-6 and tumor necrosis factor-alpha, which are pro-inflammatory and pro-thrombotic [52]. Research has shown that peri-left atrium (peri-LA) EAT is associated with both mechanical and electrical remodeling [50], as well as the incidence and prevalence of AF [50,53]. A meta-analysis by Anagnostopoulos et al. that included 12 studies with a total of 2879 patients revealed that peri-LA EAT can predict AF recurrence after ablation (Standardized Mean Difference [SMD]: −0.37). However, when examining total EAT across 12 studies with 2179 patients, no significant association was found (SMD: −0.32; 95% CI: −0.65 to 0.01). This finding needs to be interpreted with caution, as this study did not reveal any significant difference in the recurrence of AF after radiofrequency and cryoballoon ablation. The comparison between the two methods was made in a limited number of studies; specifically, three studies focused solely on cryoablation, nine were on radiofrequency, and three involved both techniques. Variations in procedural strategies, operator expertise, and patient selection could have introduced unmeasured confounding factors in this study. These findings highlight the role of peri-LA EAT in AF recurrence, as one of the predictors that deserves further research [50].

2.2.5. Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a strong predictor of recurrent AF following CA [54]. A study by Ng et al. indicates that patients with OSA have a higher AF recurrence likelihood following pulmonary vein isolation (PVI) by 25% compared to those without OSA (risk ratio 1.25, p = 0.003) [55]. In addition, OSA diagnosed by polysomnography (RR: 1.4, p < 0.001) was found to be a stronger predictor than by using the Berlin questionnaire (RR: 1.07, p < 0.001) [55]. An undiagnosed OSA can lead to a recurrence of AF after CA. Several factors may contribute to this issue, such as LA enlargement, changes in autonomic nerve activity, neurohumoral activation, and electrical remodeling of the atria. This remodeling can include slowed atrial conduction and a reduced effective refractory period in the atria [56]. CPAP therapy appears to reduce the risk of AF recurrence after CA in patients with OSA, with a risk ratio of 0.59 (p < 0.001); however, the evidence for this is deemed weak because of the small number of patients included in the studies [54]. A recent RCT conducted by Traaen et al. found that among patients with moderate to severe sleep-disordered breathing (SDB) (apnea–hypopnea index > 15) and paroxysmal AF, the administration of CPAP for five months did not reduce the AF burden [57]. There is no RCT that studied the impact of CPAP on the recurrence of AF in patients with SDB [56].

2.2.6. Physical Activity

The benefits of physical activity in reducing cardiovascular issues, including AF, are well documented. There is a U-shaped relationship between levels of physical activity and the risk of developing AF. Both participating in endurance sports and leading a sedentary lifestyle can contribute to the onset of AF [58]. According to a Mandsager et al. report, there was no discernible difference between athletes and non-athletes in the rates of AF recurrence following CA [58]. Previous studies have indicated that CA for PVI is an effective treatment option for athletes, yielding outcomes comparable to those seen in non-athletes. Athletes can typically return to sports after 4 to 6 weeks without experiencing a recurrence of AF, or they may do so once an electrophysiologic study confirms that AF is no longer inducible [59]. Liu et al. concluded that endurance athletes with AF had higher rates of arrhythmia recurrence, particularly atypical flutter, compared to non-athletes after catheter ablation [59]. The exact mechanisms behind AF in athletes are not yet fully understood. However, it is believed that they may involve structural changes in the heart, alterations in autonomic function, and chronic systemic inflammation [60]. The lower rates of successful atrial arrhythmia freedom following catheter ablation in athletes could be attributed to a less favorable underlying substrate for AF, different triggers for the condition, and the potential influence of the autonomic nervous system [59]. Exercise has the potential to prevent AF recurrence post-ablation by reducing other cardiovascular risk factors and enhancing cardiovascular health in general. However, additional data are required to fully comprehend the underlying mechanisms [59].

2.2.7. Alcohol

A dose–response relationship was discussed between alcohol consumption and the risk of AF [61]. Alcohol has also been found to be an independent predictor of the recurrence of AF post-ablation. A cut down in the alcohol intake to <30 g/week (three standard drinks) enhanced the long-term success of AF ablation, as found in the ARREST-AF study [41]. However, the Barham et al. study did not uncover any such correlation between alcohol consumption levels and post-ablation AF recurrence [62]. Recent studies have examined the impact of alcohol consumption on the recurrence of AF after CA. The findings have been mixed regarding the relationship between alcohol intake and changes in heart tissue, such as low voltage in the atria and slowed conduction [8]. A reduction in alcohol consumption by at least 1% for a year was associated with decreased AF recurrence risk post-ablation [8]. Evidence also indicates that alcohol intake is linked to an increased risk of AF recurrence following a single ablation procedure. For example, one study found that patients who consumed alcohol experienced a significantly lower success rate after a single ablation compared to those who abstained, with success rates of 79.3% versus 95.9% at 12 months, respectively [63]. Furthermore, a meta-analysis that included nine observational studies involving 5436 patients reported that moderate to high alcohol consumption was associated with a greater risk of AF recurrence post-ablation, with a summary odds ratio of 1.45 [64]. A multicenter prospective study showed that patients who limited their alcohol consumption to less than 20 g per week after ablation had better rates of AF and atrial tachycardia-free survival [63]. In summary, minimizing or eliminating alcohol consumption may significantly reduce the risk of AF recurrence following CA, which has also been endorsed by the 2024 consensus [8].

2.2.8. Chronic Kidney Disease

A meta-analysis by Lee et al. concluded that patients with chronic kidney disease (CKD) are at a statistically significant risk of AF recurrence (odds ratio (OR): 3.71). Furthermore, CKD significantly increased the risk of AF recurrence, specifically in patients with only paroxysmal AF, with an OR of 4.81. CKD was found to increase the odds of AF recurrence risk following both RFA (OR = 3.28) and cryoballoon ablation (OR = 6.50). These findings were particularly notable in the Asian population, where the OR was 4.86 [65]. Additionally, Li et al., in their meta-analysis, reported higher AF recurrence rates following a single CA procedure with a hazard ratio (HR) of 1.96. Those with 100% paroxysmal AF (all patients with paroxysmal AF) were found to have a higher risk (HR = 2.45) compared to those with non-100% paroxysmal AF (HR = 1.65) [66]. Furthermore, CKD was associated with a higher prevalence of comorbid conditions associated with AF and had larger LA dimensions. This enlargement can influence the electroanatomic substrate, leading to increased conduction disturbances. Additionally, CKD patients were found to have abnormal LA substrates, characterized by lower LA voltages and a higher prevalence of non-pulmonary vein substrates [65]. Other mechanisms include structural changes in the atria, which contribute to a higher incidence of cardiac arrhythmias. Additionally, metabolic acidosis, potassium and calcium level abnormalities, and oxidative stress also contribute to AF recurrence. Nicotinamide adenine dinucleotide phosphate oxidase and malondialdehyde, which are oxidative stress markers, have been found to be increasingly expressed in patients with CKD [66].

2.2.9. Heart Failure

In patients who have both heart failure (HF) and AF, CA has gained significant attention. Several studies and meta-analyses indicate that CA can lead to a reduced incidence of AF recurrence, lower mortality rates, and fewer hospitalizations due to HF in patients with HF with a reduced ejection fraction (HFrEF) [67,68]. Similarly, CA has been associated with a decrease in AF recurrence, mortality, and hospitalizations for HF compared to standard medical therapy [69]. In patients with HFrEF, HF-directed therapy has shown effectiveness in reducing AF recurrence and decreasing cardiovascular hospitalizations and mortality rates. While the specific impact of HF treatments on AF CA outcomes has not been extensively studied, optimizing care for underlying conditions is likely to improve AF ablation results. Therefore, it is important to adhere to guideline-recommended HF treatments for patients undergoing CA for AF [70,71,72]. A systematic review and meta-analysis involving all three categories of HF found no significant difference in AF recurrence rates after CA among the majority of ablation-naive patients with HF with reduced (HFrEF), mildly reduced (HFmrEF), and preserved (HFpEF) ejection fractions. After a median follow-up of 24 months, the recurrence rates were 40%, 35%, and 35%, respectively [73].

2.2.10. Mood Disorder

Zhuo et al., in their meta-analysis, which included 1070 patients with AF who underwent CA through circumferential PVI, found that pre-procedural depression was associated with an increased risk of AF recurrence after CA. The adjusted RR was found to be 2.24, with p < 0.001. Depression induces chronic inflammation, which is characterized by elevated interleukin-6, C-reactive protein (CRP) levels, and increased sympathetic activity. Additionally, higher aldosterone levels may contribute to the recurrence of AF following CA [74]. In a separate study by Du et al., which involved 549 AF patients who received CA, it was observed that during a mean follow-up period of 9.7 months, 216 cases (39.3%) experienced recurrent AF. This study demonstrated that anxiety independently increased the risk of AF recurrence after CA, with an adjusted RR of 2.36 (p < 0.001). Similar to depression, inflammation, activation of the renin–angiotensin-activating system (RAAS), and activated neurohormonal pathways have been implicated as the underlying drivers [75].

2.2.11. Tobacco Use

There is a very limited number of studies that have studied the association of smoking with the recurrence of AF post-ablation. In a small study (n = 59) of patients with AF who underwent PVI, smokers had a threefold higher AF recurrence risk [76]. Another retrospective study involving patients with persistent AF who underwent CA found a significantly higher non-PV trigger incidence among smokers compared to non-smokers, but no difference in the outcomes of long-term ablation was found. Mechanisms such as increased sympathetic tone, oxidative stress, inflammation, and atrial fibrosis, which are more prevalent among smokers than among non-smokers, increase the risk of AF recurrence [77].

2.2.12. Gut Microbiota

Utilizing metagenomic sequencing and metabolomic analyses, significant alterations in gut microbiota (GM) and metabolic profiles were observed between patients with recurrent AF and those without recurrence. Key discriminative taxa, including families like Nitrosomonadaceae and species such as Faecalibacterium sp CAG:82, were identified and used to develop a taxonomic scoring system. This GM-based model demonstrated a higher predictive accuracy for AF recurrence compared to traditional clinical scoring methods, suggesting that incorporating GM composition into risk assessments could enhance the stratification and management of AF patients undergoing CA [78]. Additionally, the elevated pre-procedural trimethylamine N-oxide (TMAO) level, which is a gut microbiota-derived metabolite, has been linked to higher rates of AF recurrence, highlighting the role of gut microbiota in AF progression [79]. A rise in the level of TMAO levels by 1 µM was linked to a 6% increase in the rate of AF occurrence [80]. A significant difference in serum TMAO levels, as well as increased gut flora diversity and disturbances in gut homeostasis between recurrent AF and non-recurrent AF groups, was observed by Meng et al. [79]. A reduction in fecal palmitoleic acid contributes to excessive inflammation and leads to the progression of atrial tissue’s arrhythmogenic substrate aggravation [78]. Furthermore, a reduction in Faecalibacterium abundance in the intestine may lead to increased levels of inflammatory cytokines, resulting in low-grade inflammation that contributes to the recurrence of AF [78].

2.3. Diagnostic Tests

2.3.1. Biomarkers

Following CA, there has been an association between elevated levels of specific biomarkers and increased recurrence rates of AF. Charitakis et al. identified that elevated levels of MR-proANP, caspase-8, and neurotrophin-3, which assess inflammation, fibrosis, and apoptosis, significantly increased the risk of AF recurrence [81]. Additionally, Ding et al. found that a higher neutrophil-to-lymphocyte ratio (NLR) and higher high-sensitivity C-reactive protein (hs-CRP) indicate the underlying inflammatory milieu, and these were found to predict AF recurrence independently post-CA [82]. MicroRNAs (miRNAs) have emerged as potential prognostic biomarkers for AF recurrence after catheter ablation, given their roles in atrial remodeling, inflammation, and electrical remodeling. Elevated miR-21 and reduced miR-29b-3p levels are associated with atrial fibrosis and structural changes, while lower miR-150 levels correlate with increased inflammatory activity and higher recurrence risk. Additionally, miRNAs like miR-1 and miR-328 influence electrical remodeling by modulating ion channels, impacting AF susceptibility [83]. hsa-miR-206 is a novel miRNA associated with early AF recurrence [84]. Galectin-3 (Gal-3) plays a role in fibrosis and HF. Higher levels of Gal-3 before procedures may be linked to an increased risk of AF recurrence in patients undergoing CA. This finding is supported by a meta-analysis of seven prospective cohort studies, which involved 645 AF patients and had a follow-up period of up to 18 months [85].

2.3.2. Echocardiographic Parameters

Several echocardiographic parameters have been identified as significant predictors of AF recurrence. In their study, Kim et al. found that an increased risk of late recurrence after RFA was associated with an LA diameter ≥ 45 mm, E/e′ ≥ 10, dense spontaneous echo contrast (SEC), and LA appendage flow velocity (≤40 cm/s). Decreased left ventricular function can increase LA filling pressure, eventually leading to LA dilation, promoting AF recurrence, while TEE parameters like SEC can be considered a common outcome of left atrial remodeling, fibrosis, dilation, and decreased hemodynamic function, potentially contributing to the recurrence of AF [86]. Yasuda et al. demonstrated that the LA strain is a powerful predictor of AF recurrence. Lower LA global strain (LA-GS) and a larger maximum LA volume index were significantly associated with higher recurrence rates [87]. Atrial strain parameters have been shown to correlate significantly with underlying fibrosis, providing a comprehensive real-time quantitative assessment of regional atrial myocardial deformation [88]. In a meta-analysis by Canpolat U et al. of 234 patients (81.2% paroxysmal AF) undergoing cryoballoon ablation, epicardial fat thickness (EFT) independently predicted AF recurrence (HR: 1.37, p < 0.01). A higher EFT correlated with hs-CRP levels (r = 0.381, p < 0.001), suggesting a link to systemic inflammation. An EFT ≥ 6.92 mm predicted recurrence (AUC: 0.79; sensitivity: 71.1%; specificity: 78.3%), highlighting EFT as a potential pre-procedural marker [89]. In their meta-analysis of four prospective observational studies, Correia et al. found that LA stiffness, which indicates atrial remodeling, is a strong independent predictor of AF recurrence following RFA, with an HR of 3.55 (p = 0.0002). Therefore, prior to the ablation procedure, a non-invasive assessment of LA stiffness could serve as a valuable screening tool to identify and monitor patients who are at higher risk for AF recurrence and the development of stiff LA syndrome [90].

2.3.3. Combination of Biomarkers and Echocardiographic Parameters

Combining biomarkers with echocardiographic parameters can enhance the prediction of AF recurrence. Yang et al. developed a predictive model that utilized left atrial function indexes alongside B-type natriuretic peptide (BNP) levels. This model demonstrated a superior predictive value for recurrence compared to using BNP alone [91]. Additionally, a combination of the NLR, hs-CRP, and LA diameter provided a more accurate prediction model than the biomarkers used individually [92]. In a study conducted by Ding B. et al., the combination of NLR, hs-CRP, and LA diameter achieved an area under the curve (AUC) of 0.684. In contrast, the AUC values for NLR and hs-CRP alone were 0.603 and 0.584, respectively [82]. A meta-analysis by Jarronpipatkul et al, post-CA hs-CRP was found to be significantly higher in the group that developed AF recurrence when compared to the non-recurrent group. In addition, there was no significant weighted mean difference in the baseline hs-CRP levels between both groups, highlighting that hs-CRP can predict AF recurrence [93].

2.3.4. Magnetic Resonance Imaging

Cardiac MRI (cMRI) can evaluate both the structure and function of the LA in a single examination, indicating the underlying structural remodeling that predisposes to the recurrence of AF [94]. Baek et al. confirmed that an LA dimension of ≥45 mm and a late gadolinium enhancement (LGE) of ≥25% are significant predictors of AF recurrence [95]. In predicting the AF recurrence after follow-up, LA fibrosis, which is assessed by MRI-LGE, performed very well. MRI can be used to quantify parameters like biatrial volume, LA, and RA volume, which can predict AF recurrence. Additionally, certain characteristics of the LA shape—such as having shorter, rounder, and more laterally rotated appendages—have also been identified as predictors of AF recurrence. Parameters related to LA sphericity, vertical asymmetry, and LA function impairment, as determined by cMRI, are also significantly linked to AF recurrence. These function parameters include reservoir strain, expansion index, decreased booster pump function, and also ejection fraction [94].

2.3.5. Three-Dimensional Electroanatomical Mapping

Three-dimensional mapping-guided ablation is recognized as the gold standard for treating supraventricular arrhythmias, including AF and atypical AFL. In a bipolar voltage map, areas of low voltage can indicate atrial cardiomyopathy and can be identified during the procedure using 3D electroanatomical mapping [96]. By integrating LA voltage mapping with clinical data using a multilayer perceptron, we can achieve personalized risk stratification and accurately predict the type of AF [97]. Patients with AF recurrence after 12 months had a significantly higher proportion of low-voltage areas in the LA. A threshold of <0.4 mV better reflects the arrhythmogenic substrate than the conventional value of <0.5 mV, especially when considering data from multiple mapping catheters. The extent of the low-voltage area strongly correlates with a one-year recurrence risk, which rises by 3.9% for each 1% increase in low-voltage extent on electroanatomical mapping [96]. Low-voltage areas (myocardial fibrotic degeneration) and fractionated electrograms (by diseased myocardium) secondary to the propagation of many wavefronts and/or conduction disturbances, as well as prolonged LA conduction time on high-resolution maps, were associated with recurrence [98]. A larger surface area of the posterior wall and a higher percentage of very low-voltage areas are independent predictors of AF recurrence after PVI. This correlation is likely due to structural remodeling and fibrosis. When combined, these two parameters demonstrate strong predictive power (AUC 0.900), which supports their use in pre-ablation risk stratification [99].

2.4. Atrial Fibrillation Related

2.4.1. Type of Atrial Fibrillation

AF is categorized into stages as per the 2023 ACC/AHA/ACCP/HRS guideline as those with risk factors for AF (stage 1), evidence of structural or electrical findings of predisposition to AF (stage 2), duration of AF (stage 3), which consists of paroxysmal (3A), persistent (3B), long-standing persistent AF (3B), and successful CA (3D), and permanent AF (stage 4) [3]. In paroxysmal AF, episodes of AF resolve spontaneously or through intervention within seven days of initiation. Paroxysmal AF tends to recur at a lower rate following CA compared to persistent AF [3]. In a long-term outcome study, Winkle et al. reported that the five-year AF freedom rate was 67.8% after an initial ablation and increased to 80.3% after multiple ablations in paroxysmal AF patients [100]. In contrast, persistent AF is characterized by episodes lasting longer than seven days and requiring pharmacological or electrical cardioversion for termination. Persistent AF is associated with higher recurrence rates post-ablation, with AF freedom rates of 46.6% after an initial ablation and 60.1% following multiple ablations [100]. Long-standing, persistent, continuous AF (>12 months) carries the highest recurrence rates after ablation. Winkle et al. reported that AF freedom at five years was only 30.4% after an initial ablation and improved to 43.4% with multiple procedures [100]. In the CABANA trial, CA was found to significantly reduce the recurrence of symptomatic AF, achieving an HR of 0.49 (p < 0.001). Additionally, a notable decrease in the occurrence of AF was found, with an HR of 0.52 (p < 0.001). The most common recurrent atrial arrhythmias, such as atrial tachycardia and AFL, are highly symptomatic rhythms that often require repeated CA. These rhythms are frequently observed in patients with persistent or long-standing AF [101].

2.4.2. Duration of Atrial Fibrillation

The duration of AF episodes plays a significant role in determining the likelihood of recurrence post-ablation. Shorter AF durations are associated with lower recurrence rates. Andrade et al. found that patients with AF episodes lasting less than twenty-four hours had significantly lower recurrence rates, with an HR of 0.23 with a 95% CI of 0.09–0.55, compared to those with episodes lasting more than seven days [92]. As the duration of AF episodes increases, the recurrence rates also rise. For patients with AF lasting between 24 and 48 h, the recurrence risk was found to be moderately higher, with an HR of 0.41 [84]. Similarly, episodes lasting between two to seven days demonstrated an HR of 0.25 when compared to those lasting less than twenty-four hours [92]. The highest recurrence rates were observed in patients with AF lasting longer than seven days, with a similar HR of 0.23 compared to shorter durations [92].
Long-term AF duration has also been linked to a progressive increase in recurrence risk. Yu et al. found that persistent AF lasting more than three years significantly elevated recurrence rates after CA [102]. In another study, Yubing et al. showed that patients with AF durations shorter than 24 months had a better long-term sinus rhythm maintenance rate (55.6%) compared to those with AF lasting 24 months or longer (30.4%) [103]. Additionally, Matsunaga-Lee et al. demonstrated that patients with long-standing AF persisting beyond 2.4 years had a significantly higher recurrence risk when compared to those with shorter durations, while also suggesting that additional substrate ablation (PVI-plus) was more effective than PVI alone in patients with LsAF lasting longer than 2.4 years (HR, 0.36; 95% CI, 0.14–0.89) [104].

2.5. Pharmacological Therapy

2.5.1. Antiarrhythmic Drug Use

AF management involves the use of antiarrhythmic drugs (AADs) and CA often. AADs, such as amiodarone, sotalol, and flecainide, can control the rhythm and prevent AF recurrence. However, their efficacy is limited and is significantly associated with side effects. The 2023 ACC/AHA/ACCP/HRS guidelines recommend AADs as initial therapy for rhythm control in symptomatic AF patients, but catheter ablation is preferred when AADs fail or are contraindicated [3,105].
Chen et al., in their meta-analysis, found that after the short-term use of AADs post-ablation, a significant reduction in early AF recurrence was noted. However, this reduction did not extend to the risk of late atrial arrhythmia recurrence. Furthermore, no significant decrease in the risk of late AF recurrence was observed when comparing short-term AAD to no-AAD prescription post-AF ablation [106].

2.5.2. Other Pharmacological Strategies

Sodium–Glucose Cotransporter 2 Inhibitors

Sodium–glucose cotransporter 2 inhibitors (SGLT2is) have pluripotent effects and were also shown to be effective for AF. SGLT2is have shown both direct and indirect antiarrhythmic properties, through weight loss, glucose control, and the reduction in poor cardiovascular outcomes. The DECLARE-TIMI 58 trial compared dapagliflozin with placebo among patients with T2DM and included both patients with and without HF. The dapagliflozin group exhibited a 19% reduction in AF and AFL events with an HR of 0.81 (p = 0.009) after follow-up (50.4 months) [107]. Another study that looked at the impact of SGLT2i on AF recurrence after CA among patients with T2DM and included both patients with and without HF found that it had a lower rate of AF recurrence compared to the control group (OR 0.61) after a 12-month follow-up [108].

Renin–Angiotensin–Aldosterone System Inhibitors

HTN has long been recognized as a risk factor for AF because it can lead to changes in the structure and function of the atria. It is suggested that the benefits of RAAS inhibitors in preventing the recurrence of AF may stem from a better control of HTN [109]. In a meta-analysis conducted by Zhao et al., the impact of RAAS inhibitors on the recurrence of AF after CA was examined in a cohort of 3661 patients. RAAS inhibitors were found to significantly reduce the risk of AF recurrence post-CA (adjusted OR: 0.61). Furthermore, subgroup analyses showed that both RCTs (OR, 0.35) and non-RCTs (OR, 0.76) indicated that RAAS inhibitors could effectively lower the recurrence rate of AF after CA [109]. Another meta-analysis by Peng et al. evaluated 4300 patients and similarly found that RAAS inhibitors significantly decreased AF recurrence following CA, with an RR of 0.83 (p = 0.028). Subgroup analysis revealed positive outcomes in RCTs (RR = 0.51; p < 0.001), studies conducted in Asia (RR = 0.59; p < 0.001), and studies with a follow-up duration of one year or more (RR = 0.82; p = 0.01) [110]. Additionally, a propensity score-matched (PSM) retrospective cohort study by Dong et al. explored the association between angiotensin receptor neprilysin inhibitor (ARNi) therapy and AF recurrence after RFA. This study included patients treated with ARNI and those treated with angiotensin-converting enzyme inhibitors (ACEis) (n = 155 in each). ARNi treatment was associated with a lower risk of AF recurrence compared to ACEi treatment, with an adjusted HR of 0.39 (p < 0.001) after a follow-up of 228 days (196–322) [111]. Finally, Baía Bezerra et al. conducted a meta-analysis that included three RCTs and one cohort study to evaluate the efficacy of sacubitril/valsartan in preventing AF recurrence compared to ACEis or angiotensin II receptor blockers (ARBs), and they observed that compared to the ACEi/ARB group, a significant reduction in the occurrence of persistent AF in the sacubitril/valsartan group was found (RR: 0.54; p < 0.01) [112].

Steroids

Inflammation caused by ablation can lead to acute AF recurrence, and steroid treatment is linked to a reduction in AF burden among patients who underwent CA, possibly by addressing the underlying inflammation [113,114]. In a meta-analysis conducted by Lei et al., the primary focus was on the early recurrence of AF after a single ablation procedure, with or without the use of corticosteroids after a short- and long-term follow-up. Notably, 992 patients with AF were included in this study, and they concluded that corticosteroids reduced the AF recurrence risk 3 months (OR = 0.53, p = 0.02) and 12–14 months (OR = 0.67, p = 0.02) after RFA [113]. In a meta-analysis conducted by Jaiswal et al., which included 846 patients, corticosteroids were associated with a reduced risk of AF recurrence in the analysis with RCTs (RR 0.57, p = 0.005) within one month post-CA, while it was not significant in the analysis of cohort studies, with an RR of 1.01 (p = 0.94). Furthermore, corticosteroids did not significantly influence the prevention of late AF recurrence 3 months post-ablation. This was observed in RCTs, where the RR was 0.78 (p = 0.49), and in cohort studies, where the RR was 0.96 (p = 0.78) [114].

Statins

Oxidative stress and inflammatory activation are interconnected processes that contribute to the electrical and structural remodeling of the atria. Statins affect oxidative and inflammatory mechanisms, helping to protect against the electrical remodeling associated with atrial tachycardia pacing. Specifically, atorvastatin can inhibit the generation of reactive oxygen (ROS) by downregulating NOX2, thereby protecting AF [115]. A meta-analysis conducted by Peng et al. included nine studies involving a total of 1607 patients with AF, and it was concluded that statins did not significantly reduce the recurrence rate of AF after CA. However, in the subgroup analysis of RCTs, there was a significant reduction in the recurrence of AF, with an OR of 0.47 (p = 0.001). In contrast, the retrospective cohort study subgroup reported a non-significant association with AF recurrence [115]. Statins did not show a reduction in the risk of AF recurrence after ablation, as indicated by four studies involving 750 patients. However, the use of statins was associated with a significantly lower risk of AF recurrence after electrical cardioversion, based on 12 studies involving 1790 patients (RR 0.78; p = 0.0003). When examining only RCTs, this reduction was not statistically significant, as evidenced by five studies involving 458 patients [116].

Glucagon-like Peptide Receptor-1 Agonists

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), primarily used for managing T2DM, have demonstrated significant potential for weight loss and reducing cardiovascular risk. It has been previously demonstrated that weight loss before ablation is associated with a reduced risk of AF recurrence in both obese and non-obese patients undergoing the procedure [117]. GLP-1 RAs demonstrated a significant impact on weight reduction and are associated with a lower risk of AF recurrence in both those with and without obesity post-CA [118]. A meta-analysis of three PSM studies (6031 participants), which included both patients with and without DM and HF by Karakasis P. et al., found that GLP-1 RAs significantly reduced AF recurrence post-ablation over a 12-month follow-up (HR: 0.549; p = 0.034). No significant heterogeneity was observed. The findings indicate that GLP-1 RAs may improve ablation success, necessitating further extensive randomized trials to evaluate their long-term effectiveness in sustaining sinus rhythm [118].

2.6. Catheter Ablation-Related Strategies

2.6.1. Early Catheter Ablation Strategy

Early CA has emerged as a promising strategy for managing AF. The EAST-AFNET 4 trial demonstrated that early rhythm control, including ablation, resulted in better cardiovascular outcomes compared to usual care. The EARLY-AF trial further supported this by showing that initial cryoballoon ablation was superior to AADs in preventing AF recurrence, with a significantly lower rate of arrhythmia recurrence and improved quality of life [119]. Additionally, the 2023 ACC/AHA/ACCP/HRS guidelines highlight that early ablation may prevent the progression to persistent AF [3]; it also reduces hospitalization rates and improves quality of life over a median follow-up of 3 years [3,10,119,120].
Farghaly et al. demonstrated that early RFA performed within a year of AF diagnosis was linked to lower rates of atrial arrhythmia recurrence, fewer cardiovascular hospitalizations, less progression of AF, and reduced use of AADs compared to delayed RFCA. In contrast, Kalman et al. found no significant differences in arrhythmia outcomes between early and delayed ablation strategies, but they highlighted the importance of individualized patient assessment [121,122].
Erhard et al. found that early ablation had much lower rates of arrhythmia recurrence in people under 55 years old who had persistent AF compared to late ablation [123]. Wazni et al. and Sapp et al. pointed out that controlling the rhythm early on with ablation may slow the progression to persistent AF and improve outcomes over the long term [105,124].

2.6.2. Early Recurrence

Early recurrence of atrial tachyarrhythmia (ERAT) is common after CA and is a strong predictor of late recurrence, with studies showing that patients experiencing ERAT have a significantly higher risk of late AF recurrence and symptomatic arrhythmia. The CIRCA-DOSE study found that the timing and burden of ERAT were independent predictors of late recurrence, emphasizing the need for close monitoring and potential early re-intervention [10,120]. Yanagisawa et al. evaluated the efficacy of early re-ablation for early recurrence within a blanking period after ablation and found that early re-ablation significantly reduced recurrence rates, particularly in patients with paroxysmal AF [120]. However, it is important to mention again that the blanking period as per the CIRCA-DOSE study was 52 days, while per the 2024 EHRA/HRS/APHRS/LAHRS Expert Consensus Statement, this was updated to 2 months, and recurrence within this period is considered early recurrence [8,10].

2.6.3. Ablation Strategy

PVI is still the most important part of CA for AF, which targets abnormal triggers that come from the pulmonary veins. In patients with paroxysmal AF, PVI alone is often sufficient for maintaining sinus rhythm. However, for persistent and long-lasting AF, extra ablation strategies are often needed to make the procedure more successful and lower the chance of AF happening again [125,126]. These strategies include posterior LA wall isolation, ablation of non-PV triggers, and complex fractionated atrial electrograms (CFAEs) to target areas of abnormal electrical activity contributing to arrhythmogenesis [126,127].
Recent advances in ablation techniques have aimed to achieve more durable vein isolation, minimize procedure duration, and enhance long-term freedom from AF. Early rhythm control was found to be associated with reduced mortality and stroke when compared to usual care in the EAST-AFNET 4 trial [128]. The EARLY-AF trial further supported this approach, showing that initial cryoballoon ablation was superior to AADs in preventing AF recurrence and improving quality of life [129]. The TAILORED AF trial assessed the efficacy of an AI-guided ablation strategy for patients with drug-refractory persistent AF. In this multicenter RCT, a tailored ablation procedure, AI-detected spatiotemporal electrogram dispersion with PVI ablation, was compared to a PVI-only procedure, and it was found that 88% of patients in the tailored arm achieved freedom from AF at 12 months compared to 70% in the anatomical arm (log-rank p < 0.0001 for superiority). This tailored approach necessitated longer procedure times because subsequent ablation of organized atrial tachycardias may be required to maintain long-term sinus rhythm [130].

2.6.4. Burst Pacing Post-Ablation

A meta-analysis conducted by Liu H. et al. examined the relationship between AF non-inducibility and inducibility through burst pacing following catheter ablation with respect to freedom from AF. The study found that AF non-inducibility after ablation was associated with a significantly reduced risk of AF recurrence compared to AF inducibility, with a risk ratio of 0.68 (95% CI, 0.60–0.77). Subgroup analyses indicated that these risk ratios were not significantly influenced by the type of AF (paroxysmal vs. non-paroxysmal), the duration of follow-up (≤6, 6–12, and >12 months), or the severity of burst pacing (mild, moderate, and severe) [131].

2.6.5. Ablation Technique

Thermal (Radiofrequency and Cryoballoon Ablation)

Two widely used ablation techniques are RFA and cryoballoon ablation. RFA is a point-by-point technique that delivers high-frequency energy to create continuous lesions around the PVs, effectively isolating them from the LA. In contrast, cryoballoon ablation uses cryothermal energy applied through a balloon catheter, achieving circumferential PVI in a single application per vein [105,119]. The EARLY-AF trial demonstrated that cryoballoon ablation was more effective than AADs in preventing AF recurrence at a one-year follow-up [119].
While RF ablation allows greater flexibility in targeting non-PV triggers, cryoballoon ablation offers shorter procedure times and more consistent lesion formation, particularly for paroxysmal AF [105,132]. The choice of ablation technique depends on patient-specific factors, such as LA anatomy, operator experience, and AF burden [133].

Non-Thermal (Pulsed-Field Ablation and Laser Ablation)

Non-thermal CA techniques, such as pulsed-field ablation (PFA), are characterized by cardioselectivity and reduced collateral damage to the esophagus and phrenic nerve, which are the structures adjacent to LA [134]. PFA uses high-voltage electrical pulses to create irreversible electroporation, selectively ablating cardiomyocytes while sparing non-cardiac tissues. Recent trials have demonstrated PFA’s efficacy in achieving durable PVI, with a faster procedure time and seemingly lower complication profile compared to conventional RF and cryoablation [127,135]. More prospective data are required before PFA’s long-term efficacy and safety can be determined. The efficacy and safety of PFA with conventional thermal ablation (RFA or cryoballoon ablation) in patients with drug-refractory paroxysmal AF was studied by the ADVENT trial. At one year, a composite of freedom from initial procedural failure and documented atrial tachyarrhythmia after a three-month blanking period, cardioversion, AAD use, or repeat CA was achieved in 73.3% of patients in the PFA group compared to 71.3% in the thermal ablation group. Serious adverse events related to the device and the procedure occurred in 2.1% of patients in the PFA group and in 1.5% in the thermal ablation group. PFA was found to be non-inferior to conventional thermal ablation in terms of both efficacy and safety [136].
Laser ablation was compared to RFA and cryoballoon ablation in numerous studies. In patients with persistent AF, laser ablation showed similar rates of freedom from AF one year post-ablation compared to wide-area circumferential RFA [137]. Evidence from both RCTs, along with a meta-analysis, has concluded that laser balloon ablation is similarly effective and safe when compared to cryoballoon ablation [138,139].

2.6.6. Ablation Lesion Size

The size and continuity of ablation lesions are critical determinants of procedural success. Effective lesion creation relies on factors such as catheter stability, contact force, and optimized energy delivery parameters [140]. Incomplete lesion formation can lead to PV reconnection, resulting in AF recurrence.
Jankelson et al. demonstrated that lesion-set sequentiality and mean lesion catheter excursion were independent predictors of AF recurrence, emphasizing the importance of precise lesion creation and procedural standardization [141]. The development of contact force-sensing catheters and ablation index-guided strategies has improved lesion durability, reducing recurrence rates and the need for repeat ablations [140,141]. Advancements in real-time lesion assessment tools, such as intracardiac echocardiography and electroporation mapping, have further enhanced procedural precision. Additionally, robotic catheter navigation systems have shown promise in reducing operator variability and improving long-term ablation success [141].
The EFFICAS I and EFFICAS II trials evaluated the efficacy of PVI in patients with paroxysmal AF, focusing on the impact of catheter contact force (CF) during the procedure [142,143]. EFFICAS I demonstrated a correlation between CF parameters and the durability of PVI. The study found that lower CF and force–time integral (FTI) values were associated with higher rates of electrical reconnection at follow-up, suggesting that inadequate CF during the initial procedure led to less durable isolation [142]. EFFICAS II built upon these findings by prospectively assessing the impact of CF guidance on reducing PVI gaps. Operators adhered to specific CF guidelines derived from EFFICAS I, which targets a CF of 20 g, a range of 10–30 g, and a minimum FTI of 400 g/s. The results showed a significant improvement in the durability of PVI, with 85% of PVs remaining isolated at follow-up compared to 72% in EFFICAS I (p = 0.037). Additionally, the number of lesions required during the procedure was reduced by 15% in EFFICAS II compared to EFFICAS I [143]. By incorporating CF monitoring during RF-PVI, operators can enhance the precision and durability of lesions, ultimately improving long-term clinical outcomes. These findings from EFFICAS II suggest that CF monitoring could improve patient outcomes and reduce the need for repeat procedures [143].

2.6.7. Procedural Anesthesia-Related Factors

The selection of anesthesia for CA in AF profoundly affects procedural efficiency, patient comfort, and clinical outcomes. General anesthesia is frequently preferred over conscious sedation because it ensures total immobility, thereby enabling accurate catheter manipulation, consistent application of CF, and successful lesion creation. Studies have demonstrated that GA is associated with shorter procedural times, reduced complication rates, and improved long-term success compared to conscious sedation [119,144].
Beyond its procedural advantages, GA may influence arrhythmia inducibility during ablation. Some reports suggest that GA may suppress autonomic tone, thereby affecting the detection of AF triggers, particularly non-PV sources. Conversely, conscious sedation allows for preserved autonomic function, which may be beneficial in identifying triggers during isoproterenol or adenosine challenge [145]. Despite this, most studies suggest that the benefits of stable catheter positioning, improved lesion durability, and better patient tolerability with GA outweigh the limitations associated with autonomic modulation [146].

2.7. Electroanatomical and Structural Factors

2.7.1. Left Atrial Fibrosis

Left atrial (LA) fibrosis plays a critical role in AF progression and is a strong predictor of post-ablation recurrence. The extent of atrial fibrosis can be assessed using LGE-MRI, which provides a detailed visualization of fibrotic burden. The DECAAF II study found that each 1% increase in LA fibrosis was associated with a 6% increase in AF recurrence risk following ablation, highlighting the prognostic significance of atrial structural remodeling [147].
Regional variations in fibrosis, particularly in the left atrial appendage (LAA), have been identified as important predictors of AF recurrence. Patients with extensive fibrosis may benefit from adjunctive ablation strategies, including targeting fibrotic areas or performing atrial substrate modification in addition to standard PVI [148]. While some studies advocate for extensive substrate ablation in fibrotic atria, others emphasize a more conservative approach, as excessive lesion delivery may lead to iatrogenic atrial arrhythmogenesis and mechanical dysfunction of the LA [149,150].

2.7.2. Non-Pulmonary Vein Triggers in Atrial Fibrillation Recurrence

While PVI remains the cornerstone of CA, non-PV triggers play a pivotal role in AF recurrence, particularly in persistent and long-standing, persistent AF. These ectopic foci can originate from the superior vena cava (SVC), coronary sinus, interatrial septum, LAA, and crista terminalis [128,151].
Ablation of non-PV triggers significantly improves procedural success. Studies have demonstrated that patients undergoing additional ablation of non-PV triggers experience higher rates of long-term arrhythmia-free survival compared to those receiving PVI alone [152]. Identifying non-PV triggers often requires pharmacologic provocation with high-dose isoproterenol or adenosine, which can induce latent ectopic activity [153]. In some cases, intracardiac mapping using high-density electroanatomic systems is necessary to localize and characterize non-PV foci accurately [154].
Among non-PV sites, the LAA has gained increasing attention as a significant arrhythmogenic substrate. Several studies suggest that LAA electrical isolation can enhance procedural success rates, particularly in patients with highly recurrent AF post-ablation. However, LAA isolation is associated with an increased risk of thromboembolism and requires long-term anticoagulation, necessitating careful patient selection [154,155].

2.8. Other Interventions

Renal Sympathetic Denervation

Renal sympathetic denervation (RSDN) has been shown to improve clinical outcomes for patients undergoing CA for AF, particularly those with a history of HTN. A meta-analysis by Atti et al. comprised 432 patients, including 306 with paroxysmal AF and 126 with persistent AF. The study divided participants into two groups: 186 patients received RSDN in addition to PVI, while 246 patients underwent PVI alone. The follow-up duration was at least one year. The results indicated that, compared to PVI alone, the RSDN + PVI group significantly reduced the risk of AF recurrence, with an RR of 0.58 and a 95% CI of 0.47–0.72 (p < 0.00001) during follow-up [156]. In another meta-analysis by Nawar et al., a total of 711 patients with a history of HTN and AF were assessed. This study included 329 patients undergoing PVI + RSDN and 382 patients receiving PVI alone. The findings revealed a significant reduction in AF recurrence in the PVI + RSDN group (31.3%) compared to the PVI-only group (52.9%), with a p-value of less than 0.00001 [157].

3. Future Directives and Recommendations

The recurrence of AF has remained a major clinical challenge despite the significant advances in CA. Future research and clinical efforts should focus on improving patient selection, refining ablation strategies, and incorporating novel technologies to enhance long-term success rates.

3.1. Personalizing the Risk Stratification and Prediction Model

The integration of machine learning (ML) algorithms and artificial intelligence (AI) into clinical practice will help in predicting AF recurrence more easily and accurately by combining demographical and clinical data, including comorbidities, imaging features, and biomarkers [54]. Genetic screening can also play an essential role in identifying patients with higher AF recurrence risks. Few studies have identified AF susceptibility genetic variants (e.g., 4q25 and 16q22), which may influence the ablation outcomes, although the overall impact remains uncertain [34]. The CAAP-AF score, which can standardize the prediction models, can be further validated and incorporated to enhance the patient selection process for ablation [15]. Large-scale ML-assisted registries can be used to train and validate AI models for AF recurrence prediction, and an AI-guided lesion placement algorithm can be used to improve the efficiency of ablation and reduce the number of unnecessary ablation sites.

3.2. Optimizing Ablation Strategies and Energy Modalities

PFA, which is a novel source of energy with selective cardiomyocyte electroporation, demonstrated promising outcomes for the reduction in complications while still maintaining efficacy. RCTs comparing PFA’s performance relative to traditional RFA and cryoballoon ablation are warranted [133]. Substrate-guided ablation using the LGE-MRI and high-density electroanatomic mapping may improve long-term success in patients with persistent AF [95]. Non-PV triggers, including the LAA, SVC, and posterior LA as mentioned by Hung et al. [150], can reduce AF recurrence in highly symptomatic patients. Adjunctive SGLT2i and anti-inflammatory agents can also reduce AF recurrence [47]. RCTs comparing LAA isolation vs. conventional PVI alone can be carried out to assess whether LAA ablation improves outcomes in selected populations. In addition, novel LAA-selective approaches such as electroporation, PFA, and hybrid surgical catheter techniques should be investigated. Next-generation PFA approaches enable selective atrial fibrosis remodeling, refining ablation outcomes among persistent AF patients.

3.3. Advanced Imaging and Biomarkers

Cardiac MRI can be used for pre-procedural assessment to detect atrial fibrosis through LGE and for post-ablation follow-up [147]. Echocardiographic strain analysis and left atrial function indices, such as left atrial strain and left atrial volume index, are emerging as useful tools for recurrence prediction [87]. Biomarkers such as Galectin-3, TGF-B1, NT-proBNP, and anti-inflammatory cytokines can also be explored further for recurrence prediction [81]

3.4. Lifestyle Modification and Risk Factor Management

The ARREST-AF and LEGACY trials have demonstrated that structured weight loss programs significantly improve ablation outcomes, yet additional trials are needed to refine optimal intervention thresholds [41]. OSA is a strong predictor of AF recurrence, with studies indicating that CPAP therapy reduces recurrence risk post-ablation (RR = 0.59, p < 0.001) [55]. Cardiorespiratory fitness is increasingly recognized as a modifiable factor influencing AF recurrence, but further studies are needed to assess its impact across diverse patient populations [58]. AF ablation success should not only focus on arrhythmia substrate modification but also on metabolic risk optimization.

3.5. Standardizing Definitions and Follow-Up Protocols

A universal definition of ablation success should be established beyond 12-month recurrence rates, incorporating AF burden reduction, symptom improvement, and quality-of-life metrics [7]. The optimal timing for early re-ablation in patients with early recurrence remains uncertain and should be evaluated in prospective trials [120]. The duration and role of post-ablation AAD therapy require further study, particularly in the context of long-term rhythm maintenance and atrial remodeling [3]. Moving forward, a more comprehensive definition of AF recurrence should emphasize AF burden and functional impact metrics, instead of a yes-or-no definition, as this could help better predict patient outcomes in clinical trials.

3.6. Long-Term Outcomes and Health System Considerations

Boersma et al. emphasized the importance of evaluating the cost-effectiveness of different ablation strategies, particularly as new technologies such as PFA and AI-guided ablation mapping emerge [133] on long-term outcomes, including stroke risk, HF progression, and mortality reduction, to better inform clinical decision-making [10]. Strategies for improving access to catheter ablation in underserved populations should be developed, as disparities in care may contribute to poorer outcomes [3].

4. Conclusions

In our review, we discussed modifiable and non-modifiable determinants, including clinical, lifestyle factors, and procedure-related factors that contribute to AF recurrence. Age-related atrial remodeling, female sex disparities, metabolic dysfunction, and structural heart disease predict post-ablation outcomes, emphasizing the need for tailored patient selection and planning. Weight loss, alcohol reduction, and sleep apnea management can reduce recurrence. Although antiarrhythmic drugs may provide short-term benefits after ablation, their long-term effectiveness is uncertain. Imaging biomarkers such as left atrial fibrosis, LA strain, and LA volume index in predicting the recurrence of AF are becoming increasingly relevant. Emerging evidence on substrate modification, targeting non-PV triggers, and LA appendage interventions improves outcomes in selected populations, while PVI remains the foundation of CA. PFA offers the potential for reduced collateral damage; however, long-term efficacy in various AF subtypes should be studied. The integration of AI and ML in risk stratification, procedural planning, and post-ablation monitoring holds promise for revolutionizing AF management. Future research should also focus on redefining the metrics of ablation success, moving beyond a binary definition of recurrence to a more nuanced assessment of AF burden, quality-of-life improvements, and functional outcomes. SGLT2is and GLP-1-RAs are gaining interest for their potential effects on AF risk and recurrence due to their cardioprotective and anti-fibrotic properties. As AF ablation evolves, a collaborative approach that combines technology, precision medicine, and proactive risk management is vital for improving patient outcomes and reducing the global burden of AF.

Author Contributions

Conceptualization, R.V., Q.D.H. and D.U.; methodology, A.G., M.S. and N.J.; formal analysis, K.R. and Y.M.R.; investigation, R.V., A.G. and M.S.; resources, A.N. and C.T.G.; data curation, N.J. and K.R.; writing—original draft preparation, R.V. and A.G.; writing—review and editing, M.S., Y.M.R., A.N. and C.T.G.; visualization, D.U. and Q.D.H.; supervision, C.T.G.; project administration, C.T.G. and D.U. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study as our study does not involve research on humans or identifiable data.

Acknowledgments

The Central Illustration and Figure 1 were made by Christian Toquica Gahona with the help of https://www.canva.com/help/copyright-design-ownership/ (accessed on 18 February 2025), and it is the author’s original work.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in the manuscript.
AADsAntiarrhythmic drugs
ACEIsAngiotensin-converting enzyme inhibitors
AIArtificial intelligence
AFAtrial fibrillation
ARNIAngiotensin receptor neprilysin inhibitor
BNPB-type natriuretic peptide
CACatheter ablation
CFAEComplex fractionated atrial electrogram
CKDChronic kidney disease
CPAPContinuous positive airway pressure
CVDCardiovascular disease
ERATEarly recurrence of atrial tachyarrhythmia
GAGeneral anesthesia
Gal-3Galectin-3
GMGut microbiota
HRSHeart Rhythm Society
Hs-CRPHigh-sensitivity C-reactive protein
HTNHypertension
LALeft atrial (LA)
LAALeft atrial appendage
LA-GSLeft atrium global strain
LGELate gadolinium enhancement
LsAFLong-standing persistent atrial fibrillation
miRNAsMicroRNAs
NLRNeutrophil-to-lymphocyte ratio
Non-PVNon-pulmonary vein
OSAObstructive sleep apnea
OROdds ratio
PAFParoxysmal atrial
PeAFPersistent atrial fibrillation
PFAPulsed-field ablation
PVIPulmonary vein isolation
RASRenin–angiotensin system
RCTRandomized control trial
RFRadiofrequency
RFCARadiofrequency catheter ablation
RRRelative risk
RSDNRenal sympathetic denervation
SGLT2isSodium–glucose cotransporter 2 inhibitors
SVCSuperior vena cava
T2DMType 2 diabetes mellitus

References

  1. He, J.; Zhang, Z.; Luo, D.; Yang, X.; Yang, G.; Liu, H. Atrial Fibrillation Termination as a Predictor for Persistent Atrial Fibrillation Ablation: A Systematic Review and Meta-Analysis of Prospective Studies. Cardiovasc. Ther. 2024, 2024, 9944490. [Google Scholar] [CrossRef]
  2. Guo, X.; Li, J. Risk and Protective Factors of Recurrence After Catheter Ablation for Atrial Fibrillation. Rev. Cardiovasc. Med. 2024, 25, 81. [Google Scholar] [CrossRef] [PubMed]
  3. Joglar, J.A.; Chung, M.K.; Armbruster, A.L.; Benjamin, E.J.; Chyou, J.Y.; Cronin, E.M.; Deswal, A.; Eckhardt, L.L.; Goldberger, Z.D.; Gopinathannair, R.; et al. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2023, 149, e0000000000001193. [Google Scholar] [CrossRef]
  4. Hindricks, G.; Potpara, T.; Dagres, N.; Arbelo, E.; Bax, J.J.; Blomström-Lundqvist, C.; Boriani, G.; Castella, M.; Dan, G.-A.; E Dilaveris, P.; et al. 2020 ESC Guidelines for the Diagnosis and Management of Atrial Fibrillation Developed in Collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur. Heart J. 2021, 42, 373–498. [Google Scholar] [PubMed]
  5. Stronati, G.; Guerra, F.; Urbinati, A.; Ciliberti, G.; Cipolletta, L.; Capucci, A. Tachycardiomyopathy in Patients Without Underlying Structural Heart Disease. J. Clin. Med. 2019, 8, 1411. [Google Scholar] [CrossRef]
  6. Bodagh, N.; Yap, R.; Kotadia, I.; Sim, I.; Bhalla, A.; Somerville, P.; O’neill, M.; Williams, S.E. Impact of Catheter Ablation Versus Medical Therapy on Cognitive Function in Atrial Fibrillation: A Systematic Review. J. Interv. Card. Electrophysiol. 2022, 65, 271–296. [Google Scholar] [CrossRef]
  7. Terricabras, M.; Verma, A.; Morillo, C.A. Measuring Success in Ablation of Atrial Fibrillation. Circ. Arrhythm. Electrophysiol. 2018, 11, e006582. [Google Scholar] [CrossRef]
  8. Tzeis, S.; Gerstenfeld, E.P.; Kalman, J.; Saad, E.B.; Shamloo, A.S.; Andrade, J.G.; Barbhaiya, C.R.; Baykaner, T.; Boveda, S.; Calkins, H.; et al. 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. Europace 2024, 26, euae043. [Google Scholar] [CrossRef]
  9. Shah, S.; Barakat, A.F.; Saliba, W.I.; Rehman, K.A.; Tarakji, K.G.; Rickard, J.; Bassiouny, M.; Baranowski, B.; Tchou, P.; Bhargava, M.; et al. Recurrent Atrial Fibrillation After Initial Long-Term Ablation Success. Circ. Arrhythm. Electrophysiol. 2018, 11, e005785. [Google Scholar] [CrossRef]
  10. Steinberg, C.; Champagne, J.; Deyell, M.W.; Dubuc, M.; Leong-Sit, P.; Calkins, H.; Sterns, L.; Badra-Verdu, M.; Sapp, J.; Macle, L.; et al. Prevalence and Outcome of Early Recurrence of Atrial Tachyarrhythmias in the Cryo Balloon vs Irrigated Radiofrequency Catheter Ablation (CIRCA-DOSE) Study. Heart Rhythm 2021, 18, 1463–1470. [Google Scholar] [CrossRef]
  11. Heart Rhythm Society. 2017 HRS/EHRA/ECAS/APHRS/SOLAECE Expert Consensus Statement on Catheter and Surgical Ablation of Atrial Fibrillation; Heart Rhythm Society: Washington, DC, USA, 2017; Available online: https://www.hrsonline.org/guidance/clinical-resources/2017-hrsehraecasaphrssolaece-expert-consensus-statement-catheter-and-surgical-ablation-atrial (accessed on 8 April 2025).
  12. Cleveland Clinic. Ablation of Atrial Fibrillation Outcomes|Cleveland Clinic. Available online: https://my.clevelandclinic.org/departments/heart/outcomes/393-ablation-of-atrial-fibrillation (accessed on 8 April 2025).
  13. Calkins, H.; Kuck, K.H.; Cappato, R.; Brugada, J.; Camm, A.J.; Chen, S.A.; Crijns, H.J.; Damiano, R.J.; Davies, D.W.; DiMarco, J.; et al. 2012 HRS/EHRA/ECAS Expert Consensus Statement on Catheter and Surgical Ablation of Atrial Fibrillation. J. Interv. Card. Electrophysiol. 2012, 33, 171–257. [Google Scholar] [CrossRef] [PubMed]
  14. Hussein, A.A.; Saliba, W.I.; Martin, D.O.; Bhargava, M.; Sherman, M.; Magnelli-Reyes, C.; Chamsi-Pasha, M.; John, S.; Williams-Andrews, M.; Baranowski, B.; et al. Natural History and Long-Term Outcomes of Ablated Atrial Fibrillation. Circ. Arrhythm. Electrophysiol. 2011, 4, 271–278. [Google Scholar] [CrossRef] [PubMed]
  15. Winkle, R.A.; Jarman, J.W.; Mead, R.H.; Engel, G.; Kong, M.H.; Fleming, W.; Patrawala, R.A. Predicting Atrial Fibrillation Ablation Outcome: The CAAP-AF Score. Heart Rhythm 2016, 13, 2119–2125. [Google Scholar] [CrossRef] [PubMed]
  16. MacGregor, R.M.; Khiabani, A.J.; Bakir, N.H.; Manghelli, J.L.; Sinn, L.A.; Carter, D.I.; Maniar, H.S.; Moon, M.R.; Schuessler, R.B.; Melby, S.J.; et al. Impact of Age on Atrial Fibrillation Recurrence Following Surgical Ablation. J. Thorac. Cardiovasc. Surg. 2021, 162, 1516–1528e1. [Google Scholar] [CrossRef]
  17. Bunch, T.J.; May, H.T.; Bair, T.L.; Jacobs, V.; Crandall, B.G.; Cutler, M.; Weiss, J.P.; Mallender, C.; Osborn, J.S.; Anderson, J.L.; et al. The Impact of Age on 5-Year Outcomes After Atrial Fibrillation Catheter Ablation. J. Cardiovasc. Electrophysiol. 2016, 27, 141–146. [Google Scholar] [CrossRef]
  18. Zink, M.D.; Chua, W.; Zeemering, S.; Di Biase, L.; Antoni, B.L.; David, C.; Hindricks, G.; Haeusler, K.G.; Al-Khalidi, H.R.; Piccini, J.P.; et al. Predictors of Recurrence of Atrial Fibrillation within the First 3 Months After Ablation. Europace 2020, 22, 1337–1344. [Google Scholar] [CrossRef]
  19. Leong-Sit, P.; Zado, E.; Callans, D.J.; Garcia, F.; Lin, D.; Dixit, S.; Bala, R.; Riley, M.P.; Hutchinson, M.D.; Cooper, J.; et al. Efficacy and Risk of Atrial Fibrillation Ablation Before 45 Years of Age. Circ. Arrhythm. Electrophysiol. 2010, 3, 452–457. [Google Scholar] [CrossRef]
  20. Benjamin, E.J.; Levy, D.; Vaziri, S.M.; D’Agostino, R.B.; Belanger, A.J.; Wolf, P.A. Independent Risk Factors for Atrial Fibrillation in a Population-Based Cohort: The Framingham Heart Study. JAMA 1994, 271, 840–844. [Google Scholar] [CrossRef]
  21. Sultan, A.; Lüker, J.; Andresen, D.; Kuck, K.H.; Hoffmann, E.; Brachmann, J.; Hochadel, M.; Willems, S.; Eckardt, L.; Lewalter, T.; et al. Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: Data from the German Ablation Registry. Sci. Rep. 2017, 7, 16678. [Google Scholar] [CrossRef]
  22. Kuck, K.H.; Brugada, J.; Fürnkranz, A.; Chun, K.R.J.; Metzner, A.; Ouyang, F.; Schlüter, M.; Elvan, A.; Braegelmann, K.M.; Kueffer, F.J.; et al. Impact of Female Sex on Clinical Outcomes in the FIRE AND ICE Trial of Catheter Ablation for Atrial Fibrillation. Circ. Arrhythm. Electrophysiol. 2018, 11, e006204. [Google Scholar] [CrossRef]
  23. Forleo, G.B.; Tondo, C.; De Luca, L.; Dello Russo, A.; Casella, M.; De Sanctis, V.; Clementi, F.; Fagundes, R.L.; Leo, R.; Romeo, F.; et al. Gender-Related Differences in Catheter Ablation of Atrial Fibrillation. Europace 2007, 9, 613–620. [Google Scholar] [CrossRef] [PubMed]
  24. Patel, D.; Mohanty, P.; Di Biase, L.; Sanchez, J.E.; Shaheen, M.H.; Burkhardt, J.D.; Bassouni, M.; Cummings, J.; Wang, Y.; Lewis, W.R.; et al. Outcomes and Complications of Catheter Ablation for Atrial Fibrillation in Females. Heart Rhythm 2010, 7, 167–172. [Google Scholar] [CrossRef] [PubMed]
  25. Li, Z.; Wang, Z.; Yin, Z.; Zhang, Y.; Xue, X.; Han, J.; Zhu, Y.; Zhang, J.; Emmert, M.Y.; Wang, H. Gender Differences in Fibrosis Remodeling in Patients with Long-Standing Persistent Atrial Fibrillation. Oncotarget 2017, 8, 53714–53729. [Google Scholar] [CrossRef]
  26. Li, H.; Wang, Z.; Cheng, Z.; Zhu, Y.; Yuan, Z.; Gao, J.; Zhang, X.; Wu, Y. Sex Differences Involved in Persistent Atrial Fibrillation Recurrence After Radiofrequency Ablation. BMC Cardiovasc. Disord. 2022, 22, 549. [Google Scholar] [CrossRef] [PubMed]
  27. Takigawa, M.; Kuwahara, T.; Takahashi, A.; Watari, Y.; Okubo, K.; Takahashi, Y.; Takagi, K.; Kuroda, S.; Osaka, Y.; Kawaguchi, N.; et al. Differences in Catheter Ablation of Paroxysmal Atrial Fibrillation between Males and Females. Int. J. Cardiol. 2013, 168, 1984–1991. [Google Scholar] [CrossRef]
  28. Ko, D.; Rahman, F.; Schnabel, R.B.; Yin, X.; Benjamin, E.J.; Christophersen, I.E. Atrial Fibrillation in Women: Epidemiology, Pathophysiology, Presentation, and Prognosis. Nat. Rev. Cardiol. 2016, 13, 321–332. [Google Scholar] [CrossRef]
  29. Yu, H.T.; Yang, P.S.; Kim, T.H.; Uhm, J.S.; Kim, J.Y.; Joung, B.; Lee, M.H.; Pak, H.N. Poor Rhythm Outcome of Catheter Ablation for Early-Onset Atrial Fibrillation in Women—Mechanistic Insight. Circ. J. 2018, 82, 2259–2268. [Google Scholar] [CrossRef]
  30. Feghaly, J.; Zakka, P.; London, B.; MacRae, C.A.; Refaat, M.M. Genetics of Atrial Fibrillation. J. Am. Heart Assoc. 2018, 7, e009884. [Google Scholar] [CrossRef]
  31. Shoemaker, M.B.; Muhammad, R.; Parvez, B.; White, B.W.; Streur, M.; Song, Y.; Stubblefield, T.; Kucera, G.; Blair, M.; Rytlewski, J.; et al. Common Atrial Fibrillation Risk Alleles at 4q25 Predict Recurrence After Catheter-Based Atrial Fibrillation Ablation. Heart Rhythm 2013, 10, 394–400. [Google Scholar] [CrossRef]
  32. Choe, W.S.; Kang, J.H.; Choi, E.K.; Shin, S.Y.; Lubitz, S.A.; Ellinor, P.T.; Oh, S.; Lim, H.E. A Genetic Risk Score for Atrial Fibrillation Predicts the Response to Catheter Ablation. Korean Circ. J. 2019, 49, 338–349. [Google Scholar] [CrossRef]
  33. Husser, D.; Büttner, P.; Ueberham, L.; Dinov, B.; Sommer, P.; Arya, A.; Hindricks, G.; Bollmann, A. Association of Atrial Fibrillation Susceptibility Genes, Atrial Fibrillation Phenotypes and Response to Catheter Ablation: A Gene-Based Analysis of GWAS Data. J. Transl. Med. 2017, 15, 71. [Google Scholar] [CrossRef] [PubMed]
  34. Shoemaker, M.B.; Bollmann, A.; Lubitz, S.A.; Ueberham, L.; Saini, H.; Montgomery, J.; Edwards, T.; Yoneda, Z.; Sinner, M.F.; Arya, A.; et al. Common Genetic Variants and Response to Atrial Fibrillation Ablation. Circ. Arrhythm. Electrophysiol. 2015, 8, 296–302. [Google Scholar] [CrossRef]
  35. Mohanty, S.; Hall, A.W.; Mohanty, P.; Prakash, S.; Trivedi, C.; Di Biase, L.; Santangeli, P.; Bai, R.; Burkhardt, J.D.; Gallinghouse, G.J.; et al. Novel Association of Polymorphic Genetic Variants with Predictors of Outcome of Catheter Ablation in Atrial Fibrillation: New Directions from a Prospective Study (DECAF). J. Interv. Card. Electrophysiol. 2016, 45, 7–17. [Google Scholar] [CrossRef] [PubMed]
  36. Darbar, D.; Roden, D.M. Genetic Mechanisms of Atrial Fibrillation: Impact on Response to Treatment. Nat. Rev. Cardiol. 2013, 10, 317–329. [Google Scholar] [CrossRef] [PubMed]
  37. Elliott, A.D.; Middeldorp, M.E.; Van Gelder, I.C.; Albert, C.M.; Sanders, P. Author Correction: Epidemiology and Modifiable Risk Factors for Atrial Fibrillation. Nat. Rev. Cardiol. 2023, 20, 429. [Google Scholar] [CrossRef]
  38. Santoro, F.; Di Biase, L.; Trivedi, C.; Burkhardt, J.D.; Perini, A.P.; Sanchez, J.; Horton, R.; Mohanty, P.; Mohanty, S.; Bai, R.; et al. Impact of Uncontrolled Hypertension on Atrial Fibrillation Ablation Outcome. JACC Clin. Electrophysiol. 2015, 1, 164–173. [Google Scholar] [CrossRef] [PubMed]
  39. Zylla, M.M.; Hochadel, M.; Andresen, D.; Brachmann, J.; Eckardt, L.; Hoffmann, E.; Kuck, K.-H.; Lewalter, T.; Schumacher, B.; Spitzer, S.G.; et al. Ablation of Atrial Fibrillation in Patients with Hypertension—An Analysis from the German Ablation Registry. J. Clin. Med. 2020, 9, 2402. [Google Scholar] [CrossRef]
  40. Parkash, R.; Wells, G.A.; Sapp, J.L.; Healey, J.S.; Tardif, J.-C.; Greiss, I.; Rivard, L.; Roux, J.-F.; Gula, L.; Nault, I.; et al. Effect of Aggressive Blood Pressure Control on the Recurrence of Atrial Fibrillation after Catheter Ablation: A Randomized, Open-Label Clinical Trial (SMAC-AF). Circulation 2017, 135, 1788–1798. [Google Scholar] [CrossRef]
  41. Pathak, R.K.; Middeldorp, M.E.; Lau, D.H.; Mehta, A.B.; Mahajan, R.; Twomey, D.; Alasady, M.; Hanley, L.; Antic, N.A.; McEvoy, R.D.; et al. Aggressive Risk Factor Reduction Study for Atrial Fibrillation and Implications for the Outcome of Ablation: The ARREST-AF Cohort Study. J. Am. Coll. Cardiol. 2014, 64, 2222–2231. [Google Scholar] [CrossRef]
  42. Lin, M.; Wang, J.; Rong, B.; Zhang, K.; Chen, T.; Han, W.; Hu, T.; Wang, T.; Deng, H.; Zhong, J.; et al. Impact of Diabetes Mellitus on Atrial Fibrillation Recurrence and Major Adverse Cardiac and Cerebrovascular Events Following Catheter Ablation. Int. J. Clin. Pract. 2024, 2024, 1087623. [Google Scholar] [CrossRef]
  43. Anselmino, M.; Matta, M.; D’ascenzo, F.; Pappone, C.; Santinelli, V.; Bunch, T.J.; Neumann, T.; Schilling, R.J.; Hunter, R.J.; Noelker, G.; et al. Catheter Ablation of Atrial Fibrillation in Patients with Diabetes Mellitus: A Systematic Review and Meta-Analysis. Europace 2015, 17, 1518–1525. [Google Scholar] [CrossRef]
  44. Tang, R.B.; Dong, J.Z.; Liu, X.P.; Fang, D.P.; Long, D.Y.; Liu, X.H.; Yu, R.H.; Hu, F.L.; Lu, C.S.; Hao, P.; et al. Safety and Efficacy of Catheter Ablation of Atrial Fibrillation in Patients with Diabetes Mellitus—Single Center Experience. J. Interv. Card. Electrophysiol. 2007, 17, 41–46. [Google Scholar] [CrossRef]
  45. Bogossian, H.; Frommeyer, G.; Brachmann, J.; Lewalter, T.; Hoffmann, E.; Kuck, K.H.; Andresen, D.; Willems, S.; Spitzer, S.G.; Deneke, T.; et al. Catheter Ablation of Atrial Fibrillation and Atrial Flutter in Patients with Diabetes Mellitus: Who Benefits and Who Does Not? Data from the German Ablation Registry. Int. J. Cardiol. 2016, 214, 25–30. [Google Scholar] [CrossRef]
  46. Creta, A.; Providência, R.; Adragão, P.; de Asmundis, C.; Chun, J.; Chierchia, G.; Defaye, P.; Schmidt, B.; Anselme, F.; Finlay, M.; et al. Impact of Type-2 Diabetes Mellitus on the Outcomes of Catheter Ablation of Atrial Fibrillation (European Observational Multicentre Study). Am. J. Cardiol. 2020, 125, 901–906. [Google Scholar] [CrossRef] [PubMed]
  47. Guckel, D.; Isgandarova, K.; Bergau, L.; Piran, M.; El Hamriti, M.; Imnadze, G.; Braun, M.; Khalaph, M.; Fink, T.; Sciacca, V.; et al. The Effect of Diabetes Mellitus on the Recurrence of Atrial Fibrillation after Ablation. J. Clin. Med. 2021, 10, 4863. [Google Scholar] [CrossRef] [PubMed]
  48. Liu, F.; Song, T.; Hu, Q.; Zhu, X.; Zhao, H.; Tan, Z.; Yu, P.; Ma, J.; Luo, J.; Liu, X. Body Mass Index and Atrial Fibrillation Recurrence Post Ablation: A Systematic Review and Dose-Response Meta-Analysis. Front. Cardiovasc. Med. 2023, 9, 999845. [Google Scholar] [CrossRef] [PubMed]
  49. Munger, T.M.; Dong, Y.X.; Masaki, M.; Oh, J.K.; Mankad, S.V.; Borlaug, B.A.; Asirvatham, S.J.; Shen, W.K.; Lee, H.C.; Bielinski, S.J.; et al. Electrophysiological and Hemodynamic Characteristics Associated with Obesity in Patients with Atrial Fibrillation. J. Am. Coll. Cardiol. 2012, 60, 851–860. [Google Scholar] [CrossRef]
  50. Anagnostopoulos, I.; Kousta, M.; Kossyvakis, C.; Paraskevaidis, N.T.; Vrachatis, D.; Deftereos, S.; Giannopoulos, G. Epicardial Adipose Tissue and Atrial Fibrillation Recurrence Following Catheter Ablation: A Systematic Review and Meta-Analysis. J. Clin. Med. 2023, 12, 6369. [Google Scholar] [CrossRef]
  51. Sacks, H.S.; Fain, J.N. Human Epicardial Adipose Tissue: A Review. Am. Heart J. 2007, 153, 907–917. [Google Scholar] [CrossRef]
  52. Mazurek, T.; Zhang, L.; Zalewski, A.; Mannion, J.D.; Diehl, J.T.; Arafat, H.; Sarov-Blat, L.; O’Brien, S.; Keiper, E.A.; Johnson, A.G.; et al. Human Epicardial Adipose Tissue Is a Source of Inflammatory Mediators. Circulation 2003, 108, 2460–2466. [Google Scholar] [CrossRef]
  53. Yorgun, H.; Canpolat, U.; Aytemir, K.; Hazırolan, T.; Şahiner, L.; Kaya, E.B.; Kabakci, G.; Tokgözoğlu, L.; Özer, N.; Oto, A. Association of Epicardial and Peri-Atrial Adiposity with the Presence and Severity of Non-Valvular Atrial Fibrillation. Int. J. Cardiovasc. Imaging 2015, 31, 649–657. [Google Scholar] [CrossRef] [PubMed]
  54. Charitakis, E.; Dragioti, E.; Stratinaki, M.; Korela, D.; Tzeis, S.; Almroth, H.; Liuba, I.; Jönsson, A.H.; Charalambous, G.; Karlsson, L.O.; et al. Predictors of Recurrence After Catheter Ablation and Electrical Cardioversion of Atrial Fibrillation: An Umbrella Review of Meta-Analyses. Europace 2023, 25, 40–48. [Google Scholar] [CrossRef]
  55. Ng, C.Y.; Liu, T.; Shehata, M.; Stevens, S.; Chugh, S.S.; Wang, X. Meta-Analysis of Obstructive Sleep Apnea as Predictor of Atrial Fibrillation Recurrence after Catheter Ablation. Am. J. Cardiol. 2011, 108, 47–51. [Google Scholar] [CrossRef] [PubMed]
  56. De Heide, J.; Kock-Cordeiro, D.B.; Bhagwandien, R.E.; Hoogendijk, M.G.; Van Der Meer, K.C.; Wijchers, S.A.; Szili-Torok, T.; Zijlstra, F.; Lenzen, M.J.; Yap, S. Impact of Undiagnosed Obstructive Sleep Apnea on Atrial Fibrillation Recurrence Following Catheter Ablation (OSA-AF Study). IJC Heart Vasc. 2022, 40, 101014. [Google Scholar] [CrossRef] [PubMed]
  57. Traaen, G.M.; Aakerøy, L.; Hunt, T.E.; Øverland, B.; Bendz, C.; Sande, L.Ø.; Aakhus, S.; Fagerland, M.W.; Steinshamn, S.; Anfinsen, O.G.; et al. Effect of Continuous Positive Airway Pressure on Arrhythmia in Atrial Fibrillation and Sleep Apnea: A Randomized Controlled Trial. Am. J. Respir. Crit. Care Med. 2021, 204, 573–582. [Google Scholar] [CrossRef]
  58. Mandsager, K.T.; Phelan, D.M.; Diab, M.; Baranowski, B.; Saliba, W.I.; Tarakji, K.G.; Jaber, W.A.; Kanj, M.; Tchou, P.; Lindsay, B.D.; et al. Outcomes of Pulmonary Vein Isolation in Athletes. JACC Clin. Electrophysiol. 2020, 6, 1265–1274. [Google Scholar] [CrossRef]
  59. Liu, M.B.; Lee, J.Z.; Klooster, L.; Buckner Petty, S.A.; Scott, L.R. Influence of Endurance Sports on Atrial Fibrillation Ablation Outcomes. J. Arrhythm. 2022, 38, 694–709. [Google Scholar] [CrossRef]
  60. Alexander, A.M. Atrial Fibrillation in the Athlete. Curr. Sports Med. Rep. 2013, 12, 86–92. [Google Scholar] [CrossRef]
  61. Larsson, S.C.; Drca, N.; Wolk, A. Alcohol Consumption and Risk of Atrial Fibrillation: A Prospective Study and Dose-Response Meta-Analysis. J. Am. Coll. Cardiol. 2014, 64, 281–289. [Google Scholar] [CrossRef]
  62. Barham, W.Y.; Sauer, W.H.; Fleeman, B.; Brunnquell, M.; Tzou, W.; Aleong, R.; Schuller, J.; Zipse, M.; Tompkins, C.; Nguyen, D.T. Impact of Alcohol Consumption on Atrial Fibrillation Outcomes Following Pulmonary Vein Isolation. J. Atr. Fibrillation 2016, 9, 1505. [Google Scholar] [CrossRef]
  63. Sagawa, Y.; Nagata, Y.; Miwa, N.; Yamaguchi, T.; Watanabe, K.; Kaneko, M.; Nakamura, T.; Nozato, T.; Ashikaga, T.; Goya, M.; et al. Alcohol Consumption Is Associated with Postablation Recurrence but Not Changes in Atrial Substrate in Patients with Atrial Fibrillation: Insight from a High-Density Mapping Study. J. Am. Heart Assoc. 2022, 11, e025697. [Google Scholar] [CrossRef] [PubMed]
  64. Grindal, A.W.; Sparrow, R.T.; McIntyre, W.F.; Conen, D.; Healey, J.S.; Wong, J.A. Alcohol Consumption and Atrial Arrhythmia Recurrence After Atrial Fibrillation Ablation: A Systematic Review and Meta-Analysis. Can. J. Cardiol. 2023, 39, 266–273. [Google Scholar] [CrossRef] [PubMed]
  65. Lee, W.; Wu, P.; Fang, C.; Chen, H.; Chen, M. Impact of Chronic Kidney Disease on Atrial Fibrillation Recurrence Following Radiofrequency and Cryoballoon Ablation: A Meta-Analysis. Int. J. Clin. Pract. 2021, 75, e14173. [Google Scholar] [CrossRef]
  66. Li, M.; Liu, T.; Luo, D.; Li, G. Systematic Review and Meta-Analysis of Chronic Kidney Disease as a Predictor of Atrial Fibrillation Recurrence Following Catheter Ablation. Cardiol. J. 2014, 21, 89–95. [Google Scholar] [CrossRef] [PubMed]
  67. Marrouche, N.F.; Brachmann, J.; Andresen, D.; Siebels, J.; Boersma, L.; Jordaens, L.; Merkely, B.; Pokushalov, E.; Sanders, P.; Proff, J.; et al. Catheter Ablation for Atrial Fibrillation with Heart Failure. N. Engl. J. Med. 2018, 378, 417–427. [Google Scholar] [CrossRef]
  68. AlTurki, A.; Proietti, R.; Dawas, A.; Alturki, H.; Huynh, T.; Essebag, V. Catheter Ablation for Atrial Fibrillation in Heart Failure with Reduced Ejection Fraction: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. BMC Cardiovasc. Disord. 2019, 19, 18. [Google Scholar] [CrossRef]
  69. Rattka, M.; Kuhberger, A.; Pott, A.; Stephan, T.; Weinmann, K.; Baumhardt, M.; Aktolga, D.; Teumer, Y.; Bothner, C.; Scharnbeck, D.; et al. Catheter Ablation for Atrial Fibrillation in HFpEF Patients—A Propensity-Score-Matched Analysis. J. Cardiovasc. Electrophysiol. 2021, 32, 2357–2367. [Google Scholar] [CrossRef]
  70. Rienstra, M.; Hobbelt, A.H.; Alings, M.; Tijssen, J.G.P.; Smit, M.D.; Brügemann, J.; Geelhoed, B.; Tieleman, R.G.; Hillege, H.L.; Tukkie, R.; et al. Targeted Therapy of Underlying Conditions Improves Sinus Rhythm Maintenance in Patients with Persistent Atrial Fibrillation: Results of the RACE 3 Trial. Eur. Heart J. 2018, 39, 2987–2996. [Google Scholar]
  71. Pandey, A.K.; Okaj, I.; Kaur, H.; Belley-Cote, E.P.; Wang, J.; Oraii, A.; Benz, A.P.; Johnson, L.S.B.; Young, J.; Wong, J.A.; et al. Sodium-Glucose Cotransporter Inhibitors and Atrial Fibrillation: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. J. Am. Heart Assoc. 2021, 10, e022222. [Google Scholar] [CrossRef]
  72. Olsson, L.G.; Swedberg, K.; Ducharme, A.; Granger, C.B.; Michelson, E.L.; McMurray, J.J.; Puu, M.; Yusuf, S.; Pfeffer, M.A.; CHARM Investigators. Atrial Fibrillation and Risk of Clinical Events in Chronic Heart Failure with and without Left Ventricular Systolic Dysfunction: Results from the CHARM Program. J. Am. Coll. Cardiol. 2006, 47, 1997–2004. [Google Scholar] [CrossRef]
  73. Hashem, C.; Joseph, J.; Kinlay, S.; Peralta, A.O.; Hoffmeister, P.S.; Yuyun, M.F. Atrial Fibrillation Recurrence Post-Ablation Across Heart Failure Categories: A Systematic Review and Meta-Analysis. Cardiol. Res. 2025, 16, 33–43. [Google Scholar] [CrossRef]
  74. Zhuo, C.; Ji, F.; Lin, X.; Jiang, D.; Wang, L.; Tian, H.; Xu, Y.; Liu, S.; Chen, C. Depression and Recurrence of Atrial Fibrillation After Catheter Ablation: A Meta-Analysis of Cohort Studies. J. Affect. Disord. 2020, 271, 27–32. [Google Scholar] [CrossRef]
  75. Du, H.; Yang, L.; Hu, Z.; Zhang, H. Anxiety Is Associated with Higher Recurrence of Atrial Fibrillation After Catheter Ablation: A Meta-Analysis. Clin. Cardiol. 2022, 45, 243–250. [Google Scholar] [CrossRef] [PubMed]
  76. Fukamizu, S.; Sakurada, H.; Takano, M.; Hojo, R.; Nakai, M.; Yuba, T.; Komiyama, K.; Tatsumoto, A.; Maeno, K.; Mizusawa, Y.; et al. Effect of Cigarette Smoking on the Risk of Atrial Fibrillation Recurrence After Pulmonary Vein Isolation. J. Arrhythm. 2010, 26, 21–29. [Google Scholar] [CrossRef]
  77. Cheng, W.H.; Lo, L.W.; Lin, Y.J.; Chang, S.L.; Hu, Y.F.; Hung, Y.; Chung, F.P.; Chang, T.Y.; Huang, T.C.; Yamada, S.; et al. Cigarette Smoking Causes a Worse Long-Term Outcome in Persistent Atrial Fibrillation Following Catheter Ablation. J. Cardiovasc. Electrophysiol. 2018, 29, 699–706. [Google Scholar] [CrossRef] [PubMed]
  78. Li, J.; Zuo, K.; Zhang, J.; Hu, C.; Wang, P.; Jiao, J.; Liu, Z.; Yin, X.; Liu, X.; Li, K.; et al. Shifts in Gut Microbiome and Metabolome Are Associated with Risk of Recurrent Atrial Fibrillation. J. Cell. Mol. Med. 2020, 24, 13356–13369. [Google Scholar] [CrossRef]
  79. Meng, S.; Ni, T.; Du, Q.; Liu, M.; Ge, P.; Geng, J.; Wang, B. Pre-Procedural TMAO as a Predictor for Recurrence of Atrial Fibrillation After Catheter Ablation. BMC Cardiovasc. Disord. 2024, 24, 750. [Google Scholar] [CrossRef]
  80. Yang, W.T.; Yang, R.; Zhao, Q.; Li, X.D.; Wang, Y.T. A Systematic Review and Meta-Analysis of the Gut Microbiota-Dependent Metabolite Trimethylamine N-Oxide with the Incidence of Atrial Fibrillation. Ann. Palliat. Med. 2021, 10, 11512–11523. [Google Scholar] [CrossRef]
  81. Charitakis, E.; Karlsson, L.O.; Papageorgiou, J.M.; Walfridsson, U.; Carlhäll, C.J. Echocardiographic and Biochemical Factors Predicting Arrhythmia Recurrence after Catheter Ablation of Atrial Fibrillation—An Observational Study. Front. Physiol. 2019, 10, 1215. [Google Scholar] [CrossRef]
  82. Ding, B.; Liu, P.; Zhang, F.; Hui, J.; He, L. Predicting Values of Neutrophil-to-Lymphocyte Ratio (NLR), High-Sensitivity C-Reactive Protein (Hs-CRP), and Left Atrial Diameter (LAD) in Patients with Nonvalvular Atrial Fibrillation Recurrence After Radiofrequency Ablation. Med. Sci. Monit. 2022, 28, e934569. [Google Scholar] [CrossRef]
  83. Vardas, E.P.; Oikonomou, E.; Vardas, P.E.; Tousoulis, D. MicroRNAs as Prognostic Biomarkers for Atrial Fibrillation Recurrence After Catheter Ablation: Current Evidence and Future Directions. Biomedicines 2024, 13, 32. [Google Scholar] [CrossRef] [PubMed]
  84. Šustr, F.; Macháčková, T.; Pešl, M.; Svačinova, J.; Trachtová, K.; Stárek, Z.; Kianička, B.; Slabý, O.; Novák, J. Identification of Plasmatic MicroRNA-206 as a New Predictor of Early Recurrence of Atrial Fibrillation After Catheter Ablation Using Next-Generation Sequencing. Mol. Diagn. Ther. 2024, 28, 301–310. [Google Scholar] [CrossRef] [PubMed]
  85. Zhang, G.; Wu, Y. Circulating Galectin-3 and Atrial Fibrillation Recurrence After Catheter Ablation: A Meta-Analysis. Cardiovasc. Ther. 2019, 2019, 4148129. [Google Scholar] [CrossRef] [PubMed]
  86. Kim, Y.G.; Choi, J.I.; Boo, K.Y.; Kim, D.Y.; Oh, S.K.; Park, H.S.; Lee, K.N.; Shim, J.; Kim, J.S.; Park, S.W.; et al. Clinical and Echocardiographic Risk Factors Predict Late Recurrence After Radiofrequency Catheter Ablation of Atrial Fibrillation. Sci. Rep. 2019, 9, 6890. [Google Scholar] [CrossRef]
  87. Yasuda, R.; Murata, M.; Roberts, R.; Tokuda, H.; Minakata, Y.; Suzuki, K.; Tsuruta, H.; Kimura, T.; Nishiyama, N.; Fukumoto, K.; et al. Left Atrial Strain Is a Powerful Predictor of Atrial Fibrillation Recurrence After Catheter Ablation. Eur. Heart J. Cardiovasc. Imaging 2015, 16, 1008–1014. [Google Scholar] [CrossRef]
  88. Kuppahally, S.S.; Akoum, N.; Burgon, N.S.; Badger, T.J.; Kholmovski, E.G.; Vijayakumar, S.; Rao, S.N.; Blauer, J.; Fish, E.N.; DiBella, E.V.; et al. Left Atrial Strain and Strain Rate in Patients with Paroxysmal and Persistent Atrial Fibrillation: Relationship to Left Atrial Structural Remodeling Detected by Delayed-Enhancement MRI. Circ. Cardiovasc. Imaging 2010, 3, 231–239. [Google Scholar] [CrossRef]
  89. Canpolat, U.; Aytemir, K.; Yorgun, H.; Asil, S.; Dural, M.; Özer, N. The Impact of Echocardiographic Epicardial Fat Thickness on Outcomes of Cryoballoon-Based Atrial Fibrillation Ablation. Echocardiography 2016, 33, 821–829. [Google Scholar] [CrossRef]
  90. Correia, E.T.O.; Barbetta, L.M.D.S.; Silva, O.M.P.D.; Mesquita, E.T. Left Atrial Stiffness: A Predictor of Atrial Fibrillation Recurrence after Radiofrequency Catheter Ablation—A Systematic Review and Meta-Analysis. Arq. Bras. Cardiol. 2019, 112, 501–508. [Google Scholar] [CrossRef]
  91. Yang, Z.; Xu, M.; Zhang, C.; Liu, H.; Shao, X.; Wang, Y.; Yang, L.; Yang, J. A Predictive Model Using Left Atrial Function and B-Type Natriuretic Peptide Level in Predicting the Recurrence of Early Persistent Atrial Fibrillation after Radiofrequency Ablation. Clin. Cardiol. 2021, 44, 407–414. [Google Scholar] [CrossRef]
  92. Andrade, J.G.; Deyell, M.W.; Verma, A.; Macle, L.; Champagne, J.; Leong-Sit, P.; Novak, P.; Badra-Verdu, M.; Sapp, J.; Khairy, P.; et al. Association of Atrial Fibrillation Episode Duration with Arrhythmia Recurrence Following Ablation: A Secondary Analysis of a Randomized Clinical Trial. JAMA Netw. Open 2020, 3, e208748. [Google Scholar] [CrossRef]
  93. Jaroonpipatkul, S.; Trongtorsak, A.; Kewcharoen, J.; Thangjui, S.; Pokawattana, A.; Navaravong, L. High sensitivity C reactive protein levels and atrial fibrillation recurrence after catheter ablation for atrial fibrillation: A systematic review and meta-analysis. J. Arrhythm. 2023, 39, 515–522. [Google Scholar] [CrossRef] [PubMed]
  94. Jing, M.; Li, D.; Xi, H.; Zhang, Y.; Zhou, J. Value of Imaging in the Non-Invasive Prediction of Recurrence After Catheter Ablation in Patients with Atrial Fibrillation: An Up-to-Date Review. Rev. Cardiovasc. Med. 2023, 24, 241. [Google Scholar] [CrossRef] [PubMed]
  95. Baek, Y.S.; Choi, J.I.; Kim, Y.G.; Lee, K.N.; Roh, S.Y.; Ahn, J.; Kim, D.H.; Lee, D.I.; Hwang, S.H.; Shim, J.; et al. Atrial Substrate Underlies the Recurrence after Catheter Ablation in Patients with Atrial Fibrillation. J. Clin. Med. 2020, 9, 3164. [Google Scholar] [CrossRef]
  96. Teumer, Y.; Gold, L.; Katov, L.; Bothner, C.; Rottbauer, W. Left Atrial Low-Voltage Extent Predicts the Recurrence of Supraventricular Arrhythmias. J. Cardiovasc. Dev. Dis. 2024, 11, 334. [Google Scholar] [CrossRef]
  97. An, Q.; McBeth, R.; Zhou, H.; Lawlor, B.; Nguyen, D.; Jiang, S.; Link, M.S.; Zhu, Y. Prediction of Type and Recurrence of Atrial Fibrillation After Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study. Sensors 2022, 22, 4058. [Google Scholar] [CrossRef] [PubMed]
  98. Masuda, M.; Matsuda, Y.; Uematsu, H.; Asai, M.; Okamoto, S.; Ishihara, T.; Nanto, K.; Tsujimura, T.; Hata, Y.; Higashino, N.; et al. Atrial Functional Substrates for the Prediction of Atrial Fibrillation Recurrence After Pulmonary Vein Isolation. Am. J. Cardiol. 2024, 218, 43–50. [Google Scholar] [CrossRef]
  99. Chen, Y.; Zhuang, J.; Li, X.; Zhang, C.; Cao, X.; Xu, Z.; Feng, X. The Relationship between the 3D Electroanatomical Mapping Parameters of the Left Atrial Posterior Wall and the Recurrence of Paroxysmal Atrial Fibrillation. Front. Cardiovasc. Med. 2025, 12, 1522807. [Google Scholar] [CrossRef]
  100. Winkle, R.A.; Mead, R.H.; Engel, G.; Salcedo, J.; Brodt, C.; Barberini, P.; Lebsack, C.; Kong, M.H.; Kalantarian, S.; Patrawala, R.A. Very Long-Term Outcomes of Atrial Fibrillation Ablation. Heart Rhythm 2023, 20, 680–688. [Google Scholar] [CrossRef]
  101. Poole, J.E.; Bahnson, T.D.; Monahan, K.H.; Johnson, G.; Rostami, H.; Silverstein, A.P.; Al-Khalidi, H.R.; Rosenberg, Y.; Mark, D.B.; Lee, K.L.; et al. Recurrence of Atrial Fibrillation After Catheter Ablation or Antiarrhythmic Drug Therapy in the CABANA Trial. J. Am. Coll. Cardiol. 2020, 75, 3105–3118. [Google Scholar] [CrossRef]
  102. Yu, H.T.; Kim, I.S.; Kim, T.H.; Uhm, J.S.; Kim, J.Y.; Joung, B.; Lee, M.H.; Pak, H.N. Persistent Atrial Fibrillation Over 3 Years Is Associated with Higher Recurrence After Catheter Ablation. J. Cardiovasc. Electrophysiol. 2020, 31, 457–464. [Google Scholar] [CrossRef]
  103. Wang, Y.; Xu, Y.; Ling, Z.; Chen, W.; Su, L.; Du, H.; Xiao, P.; Liu, Z.; Yin, Y. Long-Term Outcome of Radiofrequency Catheter Ablation for Persistent Atrial Fibrillation. Medicine 2018, 97, e11520. [Google Scholar] [CrossRef]
  104. Matsunaga-Lee, Y.; Inoue, K.; Tanaka, N.; Masuda, M.; Watanabe, T.; Makino, N.; Egami, Y.; Oka, T.; Minamiguchi, H.; Miyoshi, M.; et al. Duration of Atrial Fibrillation Persistence: Implications for Recurrence Risk After Catheter Ablation and Efficacy of Additional Substrate Ablation. Heart Rhythm 2024, 21, 733–740. [Google Scholar] [CrossRef] [PubMed]
  105. Wazni, O.M.; Dandamudi, G.; Sood, N.; Hoyt, R.; Tyler, J.; Durrani, S.; Niebauer, M.; Makati, K.; Halperin, B.; Gauri, A. Cryoballoon Ablation as Initial Therapy for Atrial Fibrillation. N. Engl. J. Med. 2021, 384, 316–324. [Google Scholar] [CrossRef] [PubMed]
  106. Chen, W.; Liu, H.; Ling, Z.; Xu, Y.; Fan, J.; Du, H.; Xiao, P.; Su, L.; Liu, Z.; Lan, X.; et al. Efficacy of Short-Term Antiarrhythmic Drug Use After Catheter Ablation of Atrial Fibrillation: A Systematic Review with Meta-Analyses and Trial Sequential Analyses of Randomized Controlled Trials. PLoS ONE 2016, 11, e0156121. [Google Scholar] [CrossRef]
  107. Zelniker, T.A.; Bonaca, M.P.; Furtado, R.H.M.; Mosenzon, O.; Kuder, J.F.; Murphy, S.A.; Bhatt, D.L.; Leiter, L.A.; McGuire, D.K.; Wilding, J.P.H.; et al. Effect of Dapagliflozin on Atrial Fibrillation in Patients with Type 2 Diabetes Mellitus. Circulation 2020, 141, 1227–1234. [Google Scholar] [CrossRef]
  108. Zhao, Z.; Jiang, C.; He, L.; Zheng, S.; Wang, Y.; Gao, M.; Lai, Y.; Zhang, J.; Li, M.; Dai, W.; et al. Impact of Sodium-Glucose Cotransporter 2 Inhibitor on Recurrence after Catheter Ablation for Atrial Fibrillation in Patients with Diabetes: A Propensity-Score Matching Study and Meta-Analysis. J. Am. Heart Assoc. 2023, 12, e031269. [Google Scholar] [CrossRef] [PubMed]
  109. Zhao, J.; Chen, M.; Zhuo, C.; Huang, Y.; Zheng, L.; Wang, Q. The Effect of Renin–Angiotensin System Inhibitors on the Recurrence of Atrial Fibrillation After Catheter Ablation. Int. Heart J. 2020, 61, 1174–1182. [Google Scholar] [CrossRef]
  110. Peng, L.; Li, Z.; Luo, Y.; Tang, X.; Shui, X.; Xie, X.; Zheng, Z.; Dong, R.; Liu, J.; Zhu, J.; et al. Renin–Angiotensin System Inhibitors for the Prevention of Atrial Fibrillation Recurrence After Ablation—A Meta-Analysis. Circ. J. 2020, 84, 1709–1717. [Google Scholar] [CrossRef]
  111. Dong, Y.; Xiao, S.; He, J.; Shi, K.; Chen, S.; Liu, D.; Huang, B.; Zhai, Z.; Li, J. Angiotensin Receptor–Neprilysin Inhibitor Therapy and Recurrence of Atrial Fibrillation After Radiofrequency Catheter Ablation: A Propensity-Matched Cohort Study. Front. Cardiovasc. Med. 2022, 9, 932780. [Google Scholar] [CrossRef]
  112. Baía Bezerra, F.; Rodrigues Sobreira, L.E.; Tsuchiya Sano, V.K.; de Oliveira Macena Lôbo, A.; Cavalcanti Orestes Cardoso, J.H.; Alves Kelly, F.; Aquino de Moraes, F.C.; Consolim-Colombo, F.M. Efficacy of Sacubitril–Valsartan vs. ACE Inhibitors or ARBs in Preventing Atrial Fibrillation Recurrence After Catheter Ablation: A Systematic Review and Meta-Analysis. Herz 2024, 50, 135–141. [Google Scholar] [CrossRef]
  113. Lei, M.; Gong, M.; Bazoukis, G.; Letsas, K.P.; Korantzopoulos, P.; Li, G.; Bisleri, G.; Glover, B.; Li, K.H.C.; Tse, G.; et al. Steroids Prevent Early Recurrence of Atrial Fibrillation Following Catheter Ablation: A Systematic Review and Meta-Analysis. Biosci. Rep. 2018, 38, BSR20180462. [Google Scholar] [CrossRef] [PubMed]
  114. Jaiswal, S.; Liu, X.B.; Wei, Q.C.; Sun, Y.H.; Wang, L.H.; Song, L.G.; Yang, D.D.; Wang, J.A. Effect of Corticosteroids on Atrial Fibrillation After Catheter Ablation: A Meta-Analysis. J. Zhejiang Univ. Sci. B 2018, 19, 57–64. [Google Scholar] [CrossRef]
  115. Peng, H.; Yang, Y.; Zhao, Y.; Xiao, H. The Effect of Statins on the Recurrence Rate of Atrial Fibrillation After Catheter Ablation: A Meta-Analysis. Pacing Clin. Electrophysiol. 2018, 41, 1420–1427. [Google Scholar] [CrossRef]
  116. Dentali, F.; Gianni, M.; Squizzato, A.; Ageno, W.; Castiglioni, L.; Maroni, L.; Hylek, E.M.; Grandi, A.M.; Cazzani, E.; Venco, A.; et al. Use of Statins and Recurrence of Atrial Fibrillation After Catheter Ablation or Electrical Cardioversion: A Systematic Review and Meta-Analysis. Thromb. Haemost. 2011, 106, 363–370. [Google Scholar] [CrossRef] [PubMed]
  117. Satti, D.I.; Karius, A.; Chan, J.S.K.; Isakadze, N.; Yadav, R.; Garg, K.; Aronis, K.N.; Marine, J.E.; Berger, R.; Calkins, H.; et al. Effects of Glucagon-Like Peptide-1 Receptor Agonists on Atrial Fibrillation Recurrence After Catheter Ablation. JACC Clin. Electrophysiol. 2024, 10, 1848–1855. [Google Scholar] [CrossRef]
  118. Karakasis, P.; Fragakis, N.; Patoulias, D.; Theofilis, P.; Kassimis, G.; Karamitsos, T.; El-Tanani, M.; Rizzo, M. Effects of Glucagon-Like Peptide 1 Receptor Agonists on Atrial Fibrillation Recurrence After Catheter Ablation: A Systematic Review and Meta-Analysis. Adv. Ther. 2024, 41, 3749–3756. [Google Scholar] [CrossRef]
  119. Andrade, J.G.; Wells, G.A.; Deyell, M.W.; Bennett, M.; Essebag, V.; Champagne, J.; Roux, J.-F.; Yung, D.; Skanes, A.; Khaykin, Y.; et al. Cryoablation or Drug Therapy for Initial Treatment of Atrial Fibrillation. N. Engl. J. Med. 2021, 384, 305–315. [Google Scholar] [CrossRef]
  120. Yanagisawa, S.; Inden, Y.; Kato, H.; Fujii, A.; Mizutani, Y.; Ito, T.; Kamikubo, Y.; Kanzaki, Y.; Ando, M.; Hirai, M.; et al. Effect and Significance of Early Reablation for the Treatment of Early Recurrence of Atrial Fibrillation After Catheter Ablation. Am. J. Cardiol. 2016, 118, 833–841. [Google Scholar] [CrossRef] [PubMed]
  121. Farghaly, A.A.A.; Ali, H.; Lupo, P.; Foresti, S.; De Ambroggi, G.; Atta, S.; Abdel-Galeel, A.; Tohamy, A.; Cappato, R. Early versus Late Radiofrequency Catheter Ablation in Atrial Fibrillation: Timing Matters. J. Clin. Med. 2024, 13, 4643. [Google Scholar] [CrossRef]
  122. Kalman, J.M.; Al-Kaisey, A.M.; Parameswaran, R.; Hawson, J.; Anderson, R.D.; Lim, M.; Chieng, D.; A Joseph, S.; McLellan, A.; Morton, J.B.; et al. Impact of Early vs. Delayed Atrial Fibrillation Catheter Ablation on Atrial Arrhythmia Recurrences. Eur. Heart J. 2023, 44, 2447–2454. [Google Scholar] [CrossRef]
  123. Erhard, N.; Bahlke, F.; Neuner, B.; Popa, M.; Krafft, H.; Tunsch-Martinez, A.; Syväri, J.; Tydecks, M.; Abdiu, E.; Telishevska, M.; et al. Early Ablation Leads to Better Outcome in Patients <55 Years with Persistent Atrial Fibrillation. Sci. Rep. 2024, 14, 25370. [Google Scholar] [CrossRef]
  124. Sapp, J.L.; Tang, A.S.L.; Parkash, R.; Stevenson, W.G.; Healey, J.S.; Gula, L.J.; Nair, G.M.; Essebag, V.; Rivard, L.; Roux, J.-F.; et al. Catheter Ablation or Antiarrhythmic Drugs for Ventricular Tachycardia. N. Engl. J. Med. 2024, 392, 737–747. [Google Scholar] [CrossRef] [PubMed]
  125. Natale, A.; Mohanty, S.; Sanders, P.; Anter, E.; Shah, A.; Al Mohani, G.; Haissaguerre, M. Catheter Ablation for Atrial Fibrillation: Indications and Future Perspective. Eur. Heart J. 2024, 45, 4383–4398. [Google Scholar] [CrossRef] [PubMed]
  126. Lu, Y.; Zei, P.C.; Jiang, C. Current Understanding of Atrial Fibrillation Recurrence After Atrial Fibrillation Ablation: From Pulmonary Vein to Epicardium. Pacing Clin. Electrophysiol. 2022, 45, 1216–1224. [Google Scholar] [CrossRef]
  127. Parameswaran, R.; Al-Kaisey, A.M.; Kalman, J.M. Catheter Ablation for Atrial Fibrillation: Current Indications and Evolving Technologies. Nat. Rev. Cardiol. 2021, 18, 210–225. [Google Scholar] [CrossRef]
  128. Rottner, L.; Metzner, A. Atrial Fibrillation Ablation: Current Practice and Future Perspectives. J. Clin. Med. 2023, 12, 7556. [Google Scholar] [CrossRef] [PubMed]
  129. Virk, S.A.; Chieng, D.; Segan, L.; Morton, J.B.; Lee, G.; Sparks, P.; McLellan, A.J.; Sugumar, H.; Prabhu, S.; Ling, L.-H.; et al. Incidence, Characteristics, and Prognostic Significance of Early Recurrences After Different Ablation Approaches for Persistent Atrial Fibrillation. Heart Rhythm 2024, 15, 1746–1753. [Google Scholar] [CrossRef]
  130. Deisenhofer, I.; Albenque, J.-P.; Busch, S.; Gitenay, E.; E Mountantonakis, S.; Roux, A.; Horvilleur, J.; Bakouboula, B.; Oza, S.; Abbey, S.; et al. Artificial Intelligence for Individualized Treatment of Persistent Atrial Fibrillation: A Randomized Controlled Trial. Nat. Med. 2025, 31, 1286–1293. [Google Scholar] [CrossRef]
  131. Liu, H.; Yuan, P.; Zhu, X.; Fu, L.; Hong, K.; Hu, J. Is Atrial Fibrillation Noninducibility by Burst Pacing After Catheter Ablation Associated With Reduced Clinical Recurrence?: A Systematic Review and Meta-Analysis. J. Am. Heart Assoc. 2020, 9, e015260. [Google Scholar] [CrossRef]
  132. La Rosa, G.; Quintanilla, J.G.; Salgado, R.; González-Ferrer, J.J.; Cañadas-Godoy, V.; Pérez-Villacastín, J.; Jalife, J.; Pérez-Castellano, N.; Filgueiras-Rama, D. Anatomical Targets and Expected Outcomes of Catheter-Based Ablation of Atrial Fibrillation in 2020. Pacing Clin. Electrophysiol. 2021, 44, 341–359. [Google Scholar] [CrossRef]
  133. Boersma, L. New Energy Sources and Technologies for Atrial Fibrillation Catheter Ablation. Europace 2022, 24, ii44–ii51. [Google Scholar] [CrossRef] [PubMed]
  134. Quintanilla, J.G.; Shpun, S.; Jalife, J.; Filgueiras-Rama, D. Novel Approaches to Mechanism-Based Atrial Fibrillation Ablation. Cardiovasc. Res. 2021, 117, 1662–1681. [Google Scholar] [CrossRef]
  135. Calvert, P.; Lip, G.Y.H.; Gupta, D. Radiofrequency Catheter Ablation of Atrial Fibrillation: A Review of Techniques. Trends Cardiovasc. Med. 2023, 33, 405–415. [Google Scholar] [CrossRef] [PubMed]
  136. Reddy, V.Y.; Gerstenfeld, E.P.; Natale, A.; Whang, W.; Cuoco, F.A.; Patel, C.; Mountantonakis, S.E.; Gibson, D.N.; Harding, J.D.; Ellis, C.R.; et al. Pulsed Field or Conventional Thermal Ablation for Paroxysmal Atrial Fibrillation. N. Engl. J. Med. 2023, 389, 1660–1671. [Google Scholar] [CrossRef]
  137. Schmidt, B.; Neuzil, P.; Luik, A.; Osca Asensi, J.; Schrickel, J.W.; Deneke, T.; Bordignon, S.; Petru, J.; Merkel, M.; Sediva, L.; et al. Laser Balloon or Wide-Area Circumferential Irrigated Radiofrequency Ablation for Persistent Atrial Fibrillation: A Multicenter Prospective Randomized Study. Circ. Arrhythm. Electrophysiol. 2017, 10, e005767. [Google Scholar] [CrossRef] [PubMed]
  138. Chun, J.K.R.; Bordignon, S.; Last, J.; Mayer, L.; Tohoku, S.; Zanchi, S.; Bianchini, L.; Bologna, F.; Nagase, T.; Urbanek, L.; et al. Cryoballoon versus Laser Balloon: Insights from the First Prospective Randomized Balloon Trial in Catheter Ablation of Atrial Fibrillation. Circ. Arrhythm. Electrophysiol. 2021, 14, e009294. [Google Scholar] [CrossRef]
  139. Ye, W.; Chen, Q.; Fan, G.; Zhou, X.; Wang, X.; Mao, W.; Li, J. Efficacy and Safety of Visually Guided Laser Balloon versus Cryoballoon Ablation for Paroxysmal Atrial Fibrillation: A Systematic Review and Meta-Analysis. Front. Cardiovasc. Med. 2023, 10, 1229223. [Google Scholar] [CrossRef]
  140. Jankelson, L.; Dai, M.; Bernstein, S.; Park, D.; Holmes, D.; Aizer, A.; Chinitz, L.; Barbhaiya, C. Quantitative Analysis of Ablation Technique Predicts Arrhythmia Recurrence Following Atrial Fibrillation Ablation. Am. Heart J. 2020, 220, 176–183. [Google Scholar] [CrossRef]
  141. Azzolin, L.; Eichenlaub, M.; Nagel, C.; Nairn, D.; Sanchez, J.; Unger, L.; Dössel, O.; Jadidi, A.; Loewe, A. Personalized vs. Conventional Ablation Strategies to Prevent Recurrence. Europace 2023, 25, 211–222. [Google Scholar] [CrossRef]
  142. Neuzil, P.; Reddy, V.Y.; Kautzner, J.; Petru, J.; Wichterle, D.; Shah, D.; Lambert, H.; Yulzari, A.; Wissner, E.; Kuck, K.-H. Electrical Reconnection after Pulmonary Vein Isolation Is Contingent on Contact Force During Initial Treatment: Results from the EFFICAS I Study. Circ. Arrhythm. Electrophysiol. 2013, 6, 327–333. [Google Scholar] [CrossRef]
  143. Kautzner, J.; Neuzil, P.; Lambert, H.; Peichl, P.; Petru, J.; Cihak, R.; Skoda, J.; Wichterle, D.; Wissner, E.; Yulzari, A.; et al. EFFICAS II: Optimization of Catheter Contact Force Improves Outcome of Pulmonary Vein Isolation for Paroxysmal Atrial Fibrillation. Europace 2015, 17, 1229–1235. [Google Scholar] [CrossRef]
  144. Ford, P.; Cheung, A.R.; Khan, M.S.; Rollo, G.; Paidy, S.; Hutchinson, M.; Chaudhry, R. Anesthetic Techniques for Ablation in Atrial Fibrillation: A Comparative Review. J. Cardiothorac. Vasc. Anesth. 2024, 38, 2754–2760. [Google Scholar] [CrossRef]
  145. Mountantonakis, S.E.; Elkassabany, N.; Kondapalli, L.; Marchlinski, F.E.; Mandel, J.E.; Hutchinson, M.D. Provocation of Atrial Fibrillation Triggers During Ablation: Does the Use of General Anesthesia Affect Inducibility? J. Cardiovasc. Electrophysiol. 2015, 26, 16–20. [Google Scholar] [CrossRef]
  146. Weerasooriya, R.; Shah, A.J.; Hocini, M.; Jaïs, P.; Haïssaguerre, M. Contemporary Challenges of Catheter Ablation for Atrial Fibrillation. Clin. Ther. 2014, 36, 1145–1150. [Google Scholar] [CrossRef] [PubMed]
  147. Marrouche, N.F.; Wilber, D.; Hindricks, G.; Jais, P.; Akoum, N.; Marchlinski, F.; Kholmovski, E.; Burgon, N.; Hu, N.; Mont, L.; et al. Association of Atrial Tissue Fibrosis Identified by Delayed Enhancement MRI and Atrial Fibrillation Ablation Outcome: The DECAAF Study. JAMA 2014, 311, 498–506. [Google Scholar] [CrossRef] [PubMed]
  148. Okamatsu, H.; Okumura, K. Strategy and Outcome of Catheter Ablation for Persistent Atrial Fibrillation—Impact of Progress in the Mapping and Ablation Technologies. Circ. J. 2017, 82, 2–9. [Google Scholar] [CrossRef] [PubMed]
  149. Mohanty, S.; Trivedi, C.; Gianni, C.; Della Rocca, D.G.; Morris, E.H.; Burkhardt, J.D.; Sanchez, J.E.; Horton, R.; Gallinghouse, G.J.; Hongo, R.; et al. Procedural Findings and Ablation Outcome in Patients with Atrial Fibrillation Referred after Two or More Failed Catheter Ablations. J. Cardiovasc. Electrophysiol. 2017, 28, 1379–1386. [Google Scholar] [CrossRef]
  150. Hung, Y.; Lo, L.W.; Lin, Y.J.; Chang, S.L.; Hu, Y.F.; Chung, F.P.; Tuan, T.C.; Chao, T.F.; Liao, J.N.; Walia, R.; et al. Characteristics and Long-Term Catheter Ablation Outcome in Long-Standing Persistent Atrial Fibrillation Patients with Non-Pulmonary Vein Triggers. Int. J. Cardiol. 2017, 241, 205–211. [Google Scholar] [CrossRef]
  151. Santangeli, P.; Marchlinski, F.E. Techniques for the Provocation, Localization, and Ablation of Non-Pulmonary Vein Triggers for Atrial Fibrillation. Heart Rhythm 2017, 14, 1087–1096. [Google Scholar] [CrossRef]
  152. Hwang, I.; Kwon, O.S.; Hong, M.; Yang, S.Y.; Park, J.W.; Yu, H.T.; Kim, T.H.; Uhm, J.S.; Joung, B.; Lee, M.H.; et al. Association of Genetic Polymorphisms and Extra-Pulmonary Vein Triggers in Patients with Atrial Fibrillation Who Underwent Catheter Ablation. Front. Physiol. 2021, 12, 807545. [Google Scholar] [CrossRef]
  153. Thind, M.; Oraii, A.; Chaumont, C.; Arceluz, M.R.; Sekigawa, M.; Yogasundaram, H.; Sugrue, A.; Mirwais, M.; AlSalem, A.B.; Zado, E.S.; et al. Predictors of Nonpulmonary Vein Triggers for Atrial Fibrillation: A Clinical Risk Score. Heart Rhythm 2024, 21, 806–811. [Google Scholar] [CrossRef] [PubMed]
  154. Romero, J.; Gabr, M.; Patel, K.; Briceno, D.; Diaz, J.C.; Alviz, I.; Trivedi, C.; Mohanty, S.; Polanco, D.; Della Rocca, D.G.; et al. Efficacy and safety of left atrial appendage electrical isolation during catheter ablation of atrial fibrillation: An updated meta-analysis. Europace 2021, 23, 226–237. [Google Scholar] [CrossRef] [PubMed]
  155. Di Biase, L.; Burkhardt, J.D.; Mohanty, P.; Mohanty, S.; Sanchez, J.E.; Trivedi, C.; Güneş, M.; Gökoğlan, Y.; Gianni, C.; Horton, R.P.; et al. Left atrial appendage isolation in patients with longstanding persistent AF undergoing catheter ablation. J. Am. Coll. Cardiol. 2016, 68, 1929–1940. [Google Scholar] [CrossRef] [PubMed]
  156. Atti, V.; Turagam, M.K.; Garg, J.; Lakkireddy, D. Renal Sympathetic Denervation Improves Clinical Outcomes in Patients Undergoing Catheter Ablation for Atrial Fibrillation and History of Hypertension: A Meta-Analysis. J. Cardiovasc. Electrophysiol. 2019, 30, 702–708. [Google Scholar] [CrossRef]
  157. Nawar, K.; Mohammad, A.; Johns, E.J.; Abdulla, M.H. Renal Denervation for Atrial Fibrillation: A Comprehensive Updated Systematic Review and Meta-Analysis. J. Hum. Hypertens. 2022, 36, 887–897. [Google Scholar] [CrossRef]
Figure 1. Factors influencing atrial fibrillation recurrence post-catheter ablation. AI: artificial intelligence; CA: catheter ablation; MRI: magnetic resonance imaging; PFA: pulse-field ablation; PVI: pulmonary vein isolation.
Figure 1. Factors influencing atrial fibrillation recurrence post-catheter ablation. AI: artificial intelligence; CA: catheter ablation; MRI: magnetic resonance imaging; PFA: pulse-field ablation; PVI: pulmonary vein isolation.
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Figure 2. Central Illustration: Predictors of atrial fibrillation recurrence after catheter ablation.
Figure 2. Central Illustration: Predictors of atrial fibrillation recurrence after catheter ablation.
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Vempati, R.; Garg, A.; Shah, M.; Jena, N.; Raj, K.; Reddy, Y.M.; Noheria, A.; Ha, Q.D.; Umashankar, D.; Toquica Gahona, C. Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A State-of-the-Art Review. Hearts 2025, 6, 12. https://doi.org/10.3390/hearts6020012

AMA Style

Vempati R, Garg A, Shah M, Jena N, Raj K, Reddy YM, Noheria A, Ha QD, Umashankar D, Toquica Gahona C. Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A State-of-the-Art Review. Hearts. 2025; 6(2):12. https://doi.org/10.3390/hearts6020012

Chicago/Turabian Style

Vempati, Roopeessh, Ayushi Garg, Maitri Shah, Nihar Jena, Kavin Raj, Yeruva Madhu Reddy, Amit Noheria, Quang Dat Ha, Dinakaran Umashankar, and Christian Toquica Gahona. 2025. "Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A State-of-the-Art Review" Hearts 6, no. 2: 12. https://doi.org/10.3390/hearts6020012

APA Style

Vempati, R., Garg, A., Shah, M., Jena, N., Raj, K., Reddy, Y. M., Noheria, A., Ha, Q. D., Umashankar, D., & Toquica Gahona, C. (2025). Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A State-of-the-Art Review. Hearts, 6(2), 12. https://doi.org/10.3390/hearts6020012

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