Ablation Therapy For Atrial Fibrillation Research Articles

Association between changes in cardiac function before and after ablation therapy for atrial fibrillation and concomitant sleep apnea

Association between changes in cardiac function before and after ablation therapy for atrial fibrillation and concomitant sleep apnea

The Effectiveness of Ablation Therapy for Atrial Fibrillation: A Systematic Review.

It is expected that the prevalence of atrial fibrillation (AF), the most prevalent cardiac arrhythmia among people aged 65 to 85, would be mostly classified using the CHAS2DS2-VASc approach for anticoagulation therapy. A high number of people in the entire world will be living with AF by 2030. Long-term follow-up data are sparse, although radiofrequency catheter ablation (CA) for symptomatic AF patients has the potential to be a curative therapy. Although women are referred later and less often than men, the outcomes following ablation are comparable across both genders. Health-related quality of life suffers from AF, and patients often find themselves less active as a result of their condition. AF may have a wide variety of symptoms and signs from the clinic's point of view. Women are more likely to exhibit symptoms than men; one reason for this is that women have an average QT interval that is 10-20 milliseconds longer than men, which is more likely to exacerbate tachycardia symptoms. In search of medical databases for relevant medical literature, we looked at PubMed/Medline, the Cochrane Library, and Google Scholar. Ten publications were gathered after the papers were located, assessed, and qualifying criteria applied were used to select them. The finished articles were done to give an overview of the effectiveness of ablation therapy for AF. Some studies showed that there was no statistical significance between invasive and pharmacological treatments. Other research found no difference in the recurrence of atrial arrhythmia between pulmonary vein isolation (PVI) CA alone and PVI + enhancement magnetic resonance imaging (MRI)-guided fibrosis ablation in individuals with persistent AF. The oldest individuals in studies comparing CA to medical treatment for AF demonstrated no improvement in prognosis after CA. Also, complications from therapy and CA's efficacy in preventing future atrial arrhythmias were similarly low across all age groups. Based on the above, we concluded that more studies are required to establish the most effective approach to treating AFto apply it in daily practice and gain more knowledge about it.

Association between paroxysmal or persistent atrial fibrillation and hyperuricemia in patients who underwent coronary computed tomography angiography: from the FU-CCTA-AF Registry.

Hyperuricemia (HU) and hypertension (HTN) contribute to atherosclerotic cardiovascular disease, and both are also involved in the onset and development of atrial fibrillation (AF). In the present study, we investigated the association between risk factors for atherosclerosis [including HU, HTN, blood pressure and serum uric acid (UA) levels] and paroxysmal atrial fibrillation (Paro-AF) or persistent atrial fibrillation (Pers-AF) in patients who underwent coronary computed tomography angiography (CCTA). We enrolled 263 patients from the Fukuoka University-CCTA-AF (FU-CCTA-AF Registry) who underwent CCTA prior to AF ablation therapy. AF was classified as either Paro-AF (≤ 7days) or Pers-AF (> 7days). HU was diagnosed by a serum UA level > 7.0mg/dl, and coronary artery disease (CAD) was diagnosed when CCTA results showed ≥ 50% significant coronary artery stenosis. The number of significantly diseased coronary artery vessels (VD), the Gensini score and the coronary artery calcification score (CACS) were measured. Left atrial morphology was also evaluated. Diastolic blood pressure and HbA1c in the Pers-AF group were significantly higher than those in the Paro-AF group. The Pers-AF group showed a significantly higher prevalence of HU and higher UA levels than the Paro-AF group. In a multivariate logistic regression analysis, HU was an independent associated factor to Pers-AF (odds ratio: 2.023, 95% confidence interval: 1.055-3.881, p = 0.034), while HTN was not. In patients with AF, HU is associated with Pers-AF.

Bayesian network meta-analysis comparing hot balloon, laser balloon and cryoballoon ablation as initial therapies for atrial fibrillation.

Balloon-based catheter ablation (CA) technologies, including hot balloon ablation (HBA), laser balloon ablation (LBA) and cryoballoon ablation (CBA) have been introduced in recent years as alternatives to conventional radiofrequency ablation therapy for atrial fibrillation (AF). However, the results remain controversial concerning the optimal approach. Thus, we conducted a network meta-analysis (NMA) to comprehensively evaluate the efficacy and safety of HBA, LBA and CBA. Clinical trials comparing the efficacy and safety of HBA, LBA and CBA were identified through a systematic search up to October 2022. The primary outcomes of interest were the recurrence of AF and procedure-related complications. Twenty clinical trials with a total of 1,995 patients were included in the meta-analysis. The NMA results demonstrated that HBA, LBA and CBA had comparable AF recurrence rates (HBA vs. CBA: odds ratio OR = 0.88, 95% credible interval CrI: 0.56-1.4; LBA vs. CBA: OR = 1.1, 95% CrI: 0.75-1.5; LBA vs. HBA: OR = 1.2, 95% CrI: 0.70-2.0) and procedure-related complications (HBA vs. CBA: OR = 0.93, 95% CrI: 0.46-2.3; LBA vs. CBA: OR = 1.1, 95% CrI: 0.63-2.1; LBA vs. HBA: OR = 1.2, 95% CrI: 0.44-2.8). The surface under the cumulative ranking curve (SUCRA) suggested that HBA may be the optimal approach concerning the primary outcomes (SUCRA = 74.4%; 61.1%, respectively). However, HBA (40.1%) had a significantly higher incidence of touch-up ablation (TUA) than LBA (8.5%, OR = 2.8, 95% CrI: 1.1-7.1) and CBA (11.9%, OR = 3.7, 95% CrI: 1.9-7.5). LBA required more procedure time than CBA [mean difference (MD = 32.0 min, 95% CrI: 19.0-45.0 min)] and HBA (MD = 26.0 min, 95% CrI: 5.6-45.0 min), but less fluoroscopy time than HBA (MD = -9.4 min, 95% CrI: -17.0--2.4 min). HBA, LBA and CBA had comparable efficacy and safety as initial treatments for AF. HBA ranked highest in the primary outcomes, but at the cost of a higher incidence of TUA and longer fluoroscopy time. www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022381954, identifier: CRD42022381954.

Safety of Catheter Ablation Therapy for Atrial Fibrillation in Cardiac Amyloidosis.

Background Despite the high burden of atrial fibrillation in cardiac amyloidosis (CA), the safety of catheter ablation therapy in CA is not well established. We sought to examine short-term safety outcomes following atrial fibrillation ablation in patients with CA compared with matched patients with dilated cardiomyopathy (DCM). Methods and Results Using data from the National Inpatient Sample, we identified all hospitalizations for atrial fibrillation ablation from the fourth quarter of 2015 through 2019. Admissions for CA and DCM were matched in a 1:5 ratio using propensity scores based on the following sociodemographics: age, sex, race or ethnicity, payor, median income, comorbidities, and hospital characteristics. We compared in-hospital outcomes between both cardiomyopathies. We identified 1395 unweighted hospitalizations (representing 6750 national hospitalizations) for atrial fibrillation ablation, out of which 45 (3.2%) were admissions for CA. Compared with DCM, patients with CA were older (72.9 versus 65.1 years), had a higher burden of prior stroke (20.0% versus 8.6%) and chronic kidney disease (53.3% versus 33.6%), and were less likely to have a prior implantable cardioverter-defibrillator (4.4% versus 23.0%). We successfully matched 42 CAs to 210 DCM hospitalizations. After matching, there was no difference in total complications (14.3% versus 10.5%, P=0.60), length-of-stay (3.1 versus 2.1 days, P=0.23), home disposition (97.6% versus 96.2%, P=0.65), and total charges ($137 250 versus $133 910, P=0.24). Conclusions In this nationally representative study of atrial fibrillation catheter ablation in CA, short-term safety outcomes and complication rates were similar to a propensity score-matched cohort of DCM. Further studies exploring long-term safety outcomes are needed.

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

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

Incidence, types and predictors of AF recurrence after AF ablation with pulsed field ablation. A single-centre experience

Abstract Funding Acknowledgements Type of funding sources: None. Background Pulsed field ablation (PFA) is an emerging method for atrial fibrillation (AF) ablation. However, there is little data about incidence, types, and predictors of AF recurrences after PFA for AF ablation. Methods We report our single-centre experience with PFA for AF ablation. Each procedure was performed under unconscious sedation with propofol and fentanyl. If needed, midazolam was added in rare cases. Fifteen minutes before transeptal puncture 70IU/kg of unfractionated heparin were administered, for an ACT level >300sec during the entire procedure. Isolation of pulmonary veins was started after administration of 1mg of atropine with 8 applications per vein (4 in basket, 4 in flower configuration). Afterwards all veins were checked for entrance- and exitblock to confirm isolation during SR. If needed, additional ablation was performed. Results In total, 124 patients undergoing AF ablation therapy with PFA between June 2021 to October 2022 were analysed. Mean age was 61±9 years, 39% were female. Mean CHADS-VASc Score was 2±1. Sixty-two percent had paroxysmal atrial fibrillation (PAF), 34% persistent AF, in 4% patients suffered from long standing persistent AF. In 85% (n=106) of procedures first pass isolation of all veins was possible. Primary success to achieve PV isolation was accomplished in all patients at the end of procedure. In addition to PVI, in 6,5% of patients cavotricuspid isthmus (CTI) was blocked, in another 7,3% the posterior wall was isolated during the first procedure. Mean procedure duration was 76±30 minutes, mean x-ray time 11±22 minutes. During 124 procedures, only one periprocedural complication was documented (vascular complication). Eighteen patients (14,5%) had recurrence of dysrhythmia after a blanking period of 3 months after a mean follow-up period of 167±150 days. Mean time to recurrence was 108±101 days. Patients with recurrences after the blanking period suffered significantly more often from diabetes (OR 0,21 (0,089-0,495); p>0.01) and hyperlipidaemia (OR: 0,198 (0,070-0,498); p>0.01). Until now we performed five re-do procedures of patients with recurrence of dysrhythmia after a PFA first-do procedure. The recurrent arrhythmia was AF (n=2), atypical AT (roof-dependent n=1, one mitral isthmus dependent n=1), and CTI-dependent flutter (n=1). All five patients had PV reconnections, and all could be successfully reablated. Conclusion AF ablation with PFA is associated with high SR success rate, and acceptable procedure duration and complication rates. Randomized studies are needed to further evaluate this new method compared with other ablation techniques.

Exploring interpretability in deep learning prediction of successful ablation therapy for atrial fibrillation.

Background: Radiofrequency catheter ablation (RFCA) therapy is the first-line treatment for atrial fibrillation (AF), the most common type of cardiac arrhythmia globally. However, the procedure currently has low success rates in dealing with persistent AF, with a reoccurrence rate of ∼50% post-ablation. Therefore, deep learning (DL) has increasingly been applied to improve RFCA treatment for AF. However, for a clinician to trust the prediction of a DL model, its decision process needs to be interpretable and have biomedical relevance. Aim: This study explores interpretability in DL prediction of successful RFCA therapy for AF and evaluates if pro-arrhythmogenic regions in the left atrium (LA) were used in its decision process. Methods: AF and its termination by RFCA have been simulated in MRI-derived 2D LA tissue models with segmented fibrotic regions (n = 187). Three ablation strategies were applied for each LA model: pulmonary vein isolation (PVI), fibrosis-based ablation (FIBRO) and a rotor-based ablation (ROTOR). The DL model was trained to predict the success of each RFCA strategy for each LA model. Three feature attribution (FA) map methods were then used to investigate interpretability of the DL model: GradCAM, Occlusions and LIME. Results: The developed DL model had an AUC (area under the receiver operating characteristic curve) of 0.78 ± 0.04 for predicting the success of the PVI strategy, 0.92 ± 0.02 for FIBRO and 0.77 ± 0.02 for ROTOR. GradCAM had the highest percentage of informative regions in the FA maps (62% for FIBRO and 71% for ROTOR) that coincided with the successful RFCA lesions known from the 2D LA simulations, but unseen by the DL model. Moreover, GradCAM had the smallest coincidence of informative regions of the FA maps with non-arrhythmogenic regions (25% for FIBRO and 27% for ROTOR). Conclusion: The most informative regions of the FA maps coincided with pro-arrhythmogenic regions, suggesting that the DL model leveraged structural features of MRI images to identify such regions and make its prediction. In the future, this technique could provide a clinician with a trustworthy decision support tool.

Can artificial intelligence prediction of successful atrial fibrillation catheter ablation therapy be interpretable?

Abstract Background Radiofrequency catheter ablation (RFCA) therapy is the first-line treatment for atrial fibrillation (AF), the most common type of cardiac arrhythmia globally. However, the procedure currently has low success rates in dealing with persistent AF, with a reoccurrence rate of ∼50% post-ablation. Therefore, artificial intelligence (AI), particularly deep learning (DL), has increasingly been applied to improve and optimise treatments for AF. However, AI is limited by its black-box nature. Therefore, a factor hindering the broad clinical application of DL in AF is the lack of assurance that the DL model is using physiological relevant features when making its prediction. In order to provide this assurance, its decision process needs to be interpretable and have biomedical relevance. Aim This study aims to explore interpretability in DL prediction of successful ablation therapy for AF and evaluate if pro-arrhythmogenic regions in the left atrium (LA) were used in its decision process. Methods LA models with segmented fibrotic tissue were derived from 122 late gadolinium-enhanced magnetic resonance (LGE MR) images of persistent AF patients. To increase the dataset size, an additional 199 synthetic LA tissue models were generated from the LGE MR images. Two ablation strategies were simulated: fibrosis-based ablation (FIBRO) and a rotor-based ablation (ROTOR). RFCA strategy success was determined by its ability to terminate persistent AF in 2s with less than 40% of the tissue ablated [1]. A convolutional neural network (CNN) was developed to predict the success of each RFCA strategy, and gradient weighted class activation maps (GradCAM) were used to assess if the CNN was using locations of pro-arrhythmogenic regions in its decision process on an independent test set of 50 LA tissue models. Results For predicting the success of the FIBRO strategy, the CNN model had an AUC (area under the receiver operating characteristic curve) of 0.92±0.02, recall of 0.89±0.03 and precision of 0.82±0.02. For the ROTOR strategy, the AUC was 0.77±0.02, the recall was 0.93±0.04 and the precision was 0.76±0.02. Finally, the independent test set's GradCAM saliency maps showed that 62±25% and 71±13% of ablation lesions (known from the LA model simulations, but unseen by the CNN during training) coincided with informative regions in the saliency maps for the FIBRO and ROTOR strategies, respectively (Figure 1). Conclusion The most informative regions of the saliency maps coincided with the successful ablation lesions, suggesting that the DL model was able to identify ablated pro-arrhythmogenic regions by leveraging structural features of LGE MR images. In the future, this technique could provide a clinician with a decision support tool and increase confidence in the AI prediction. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UK Medical Research Council

Abstract 10321: Safety of Catheter Ablation Therapy for Atrial Fibrillation in Cardiac Amyloidosis

Introduction: Despite a high burden of atrial fibrillation (AF) in cardiac amyloidosis (CA), the safety of catheter ablation therapy (CAT) in CA is not well established. We sought to examine short-term safety outcomes following CAT for AF in patients with CA compared to matched patients with dilated cardiomyopathy (DCM). Methods: Using data from National Inpatient Sample (NIS), we identified all hospitalizations for AF CAT from the fourth quarter of 2015 through 2019. We matched CA to DCM admissions in a 1:5 ratio using propensity scores based on sociodemographic, clinical comorbidities, and hospital characteristics. We compared in-hospital outcomes including mortality, procedural complications, discharge disposition, total charges, and length-of-stay Results: Overall, 1,395 unweighted hospitalizations (representing 6,750 national hospitalizations) for AF CAT were included in analysis, out of which 45 (3.2%) were admissions for CA. Compared to DCM, CA patients were older (72.9years vs 65.1years), had a higher burden of prior stroke (20.0% vs 8.6%) and chronic kidney disease (53.3% vs 33.6%), and were less likely to have a prior ICDs (4.4% vs 23.0%). We matched 42 amyloid hospitalizations to 210 DCM hospitalizations. After matching, there was no difference in rate of in-hospital mortality (0.24 vs 0.33%, p=0.77), home disposition (97.6% vs 96.2%, p=0.65), total procedural complications (14.3% vs 10.5%, p=0.60), length-of-stay (3.1 days vs 2.1 days, p = 0.23) and total hospital charges ($137,250 vs $133,910, p=0.24). Conclusions: In this contemporary study of CAT for AF in CA, short-term safety outcomes and complication rates were similar to a propensity-score-matched cohort of DCM. Further studies exploring long-term safety outcomes are needed.

High epicardial fat volume is associated with atrial fibrillation recurrences after catheter ablation

Abstract Background Pulmonary vein isolation (PVI) is the cornerstone of catheter ablation therapy for atrial fibrillation (AF). However, even with important technological improvements, AF recurrences are common in long-term follow-up. Recently, epicardial fat tissue (EFT) has been proposed as a potential AF modulator promoting and sustaining atrial arrhythmogenic milieu. Aim In this retrospective single-centre study, we sought to evaluate the association between CT-quantified EFT volume and long-term primary PVI outcome assed by means of continuous ECG monitoring with implantable loop recorders (ILR) in paroxysmal AF patients. Methods A cohort of 92 patients (median age 60.2 [IQR 51.9–64.0]; 74% male) with paroxysmal AF (a single persistent AF episode was accepted) undergoing catheter ablation targeted at PVI was analysed. Prior to CA all patients underwent cardiac CT imaging with subsequent implantation of implantable loop recorder (ILR). Radiofrequency CA ablation with electro-anatomical mapping for PVI was used in 79 patients, balloon cryoablation was used in 13 patients. Verified complete PVI was defined as procedural endpoint. EFT volume was semi-automatically segmented and quantified on contrast enhanced CT studies. AF recurrence, defined as AF burden >0.1% after the blanking period (90 days), was continuously assessed by ILR. Kaplan-Meier analysis of AF recurrence-free survival at 1-year, 2-year and 3-year follow-up periods compared patients stratified into EFT volume tertiles. Results During a median follow-up of 52.6 months [IQR 43–64], AF recurrence was detected in 58 (63%) patients, 29 (50%) of them underwent a repeat ablation. Patients in high, mid, and low total EFT volume tertiles had a median time to late AF recurrence of 154, 373, and 284 days (Fig. 1A). At a 1-year follow-up, patients in the high EFT volume tertile had the worst AF ablation outcome (p=0.023). However, this difference gradually faded-out and became non-significant at 2 and 3 years. ROC analysis revealed an EFT of 95 ml as an optimal cut-off (p=0.002) for expected arrhythmia recurrence post acutely successful PVI (Fig. 1B). Conclusion EFT volume quantification in a relatively homogenous, continuously monitored cohort of patients undergoing catheter ablation for paroxysmal AF revealed a significant association between AF recurrence at 1 year post ablation and volume of epicardial fat. These results suggest a possible role of epicardial adipose tissue as an adverse pro-fibrillatory factor. Identified EFT volume cut-offs have to be validated prospectively on a larger and balanced patient population. Funding Acknowledgement Type of funding sources: None.

Can artificial intelligence prediction of successful atrial fibrillation catheter ablation therapy be interpretable?

Abstract Background Radiofrequency catheter ablation (RFCA) therapy is the first-line treatment for atrial fibrillation (AF), the most common type of cardiac arrhythmia globally. However, the procedure currently has low success rates in dealing with persistent AF, with a reoccurrence rate of ∼50% post-ablation. Therefore, artificial intelligence (AI), particularly deep learning (DL), has increasingly been applied to improve and optimise treatments for AF. However, AI is limited by its black-box nature. Therefore, a factor hindering the broad clinical application of DL in AF is the lack of assurance that the DL model is using physiological relevant features when making its prediction. In order to provide this assurance, its decision process needs to be interpretable and have biomedical relevance. Aim This study aims to explore interpretability in DL prediction of successful ablation therapy for AF and evaluate if pro-arrhythmogenic regions in the left atrium (LA) were used in its decision process. Methods LA models with segmented fibrotic tissue were derived from 122 late gadolinium-enhanced magnetic resonance (LGE MR) images of persistent AF patients. To increase the dataset size, an additional 199 synthetic LA tissue models were generated from the LGE MR images. Two ablation strategies were simulated: fibrosis-based ablation (FIBRO) and a rotor-based ablation (ROTOR). RFCA strategy success was determined by its ability to terminate persistent AF in 2s with less than 40% of the tissue ablated [1]. A convolutional neural network (CNN) was developed to predict the success of each RFCA strategy, and gradient weighted class activation maps (GradCAM) were used to assess if the CNN was using locations of pro-arrhythmogenic regions in its decision process on an independent test set of 50 LA tissue models. Results For predicting the success of the FIBRO strategy, the CNN model had an AUC (area under the receiver operating characteristic curve) of 0.92±0.02, recall of 0.89±0.03 and precision of 0.82±0.02. For the ROTOR strategy, the AUC was 0.77±0.02, the recall was 0.93±0.04 and the precision was 0.76±0.02. Finally, the independent test set's GradCAM saliency maps showed that 62±25% and 71±13% of ablation lesions (known from the LA model simulations, but unseen by the CNN during training) coincided with informative regions in the saliency maps for the FIBRO and ROTOR strategies, respectively (Figure 1). Conclusion The most informative regions of the saliency maps coincided with the successful ablation lesions, suggesting that the DL model was able to identify ablated pro-arrhythmogenic regions by leveraging structural features of LGE MR images. In the future, this technique could provide a clinician with a decision support tool and increase confidence in the AI prediction. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UK Medical Research Council

S2384 The First Case of Water Immersion Endoscopy in the Definitive Diagnosis of Atrio: Esophageal Fistula

Introduction: Atrial fibrillation (AF) is the most common heart rhythm disorder with estimated global prevalence of 33.5 million. Catheter ablation is the treatment modality of choice for refractory AF. Atrio-esophageal fistula (AEF) is a serious complication of catheter ablation. Diagnosis is critical to the management of AEF, and includes computed tomography of the chest, esophagram and esophagogastroduodenoscopy (EGD). Prompt diagnosis of AEF is essential for survival. Case Description/Methods: A 56-year-old male with AF presented with fever, fatigue and bilateral leg weakness. Twenty days prior to presentation he underwent pulmonary vein isolation radiofrequency ablation and discharged the following day. Upon re-presentation his vitals were notable for fever and tachycardia. Labs revealed a normal white count and hemoglobin, and elevated lactate and troponin. One hour after arrival he developed complex focal seizure and AF with rapid ventricular rate followed by respiratory decompensation requiring intubation. His blood cultures revealed Streptococcus mitis and Gemella haemolysans. His MRI disclosed numerous bilateral emboli concerning for endocarditis, however TEE did not reveal any valvular vegetation, thus proposing AEF as a possible complication accounting for the emboli. CT chest angiogram revealed subtle irregularity along the posterior wall of the left atrium (figure A), but did not provide conclusive evidence to warrant high-risk cardiothoracic surgery. Water immersion EGD was performed to diagnose and localize the fistula, revealing esophageal defect in the proximal esophagus with movement of non-bloody debris through the tract (figure B). One hemostatic clip was placed near the tract to assist with localization for surgical closure. The following day the patient underwent right thoracotomy with placement of intercostal muscle flap to fistula (Figure C). Discussion: AEF is a rare complication of radiofrequency ablation therapy for AF. High mortality rate is primarily attributed to major cerebrovascular morbidity from septic thrombi. Currently there is no effective modality to visualize AEF safely and reliably. Water immersion colonoscopy allows for completion of difficult colonoscopies, decreased insertion pain, and increased adenoma-detection rates. This technique was applied to identify the AEF. Water immersion EGD is an important modality that can confidently be considered within the diagnostic armamentarium of gastroenterologists to ensure safe and rapid diagnosis and treatment of AEF.Figure 1.: 1: (A) Illustrates a subtle contour abnormality involving the posterior wall of the left atrium (arrow) concerning for AEF (B) Water immersion endoscopy illustrating 3mm defect (arrow) in the wall of the esophagus (C) Underwent right thoracotomy to access AEF. This image highlights 3mm fistula site (arrow) that is approximated to be at the midpoint of the atrium.

Safety, Readmissions, and Cost-Effectiveness of Same-Day Discharge vs. Overnight Stay Following Ablation Therapy for Atrial Fibrillation

Safety, Readmissions, and Cost-Effectiveness of Same-Day Discharge vs. Overnight Stay Following Ablation Therapy for Atrial Fibrillation

A Chronicle of Hybrid Atrial Fibrillation Ablation Therapy: From Cox Maze to Convergent.

The burden of AF is increasing in prevalence and healthcare resource usage in the UK and worldwide. It can result in impaired quality of life for affected patients, as well as increased risk of stroke, heart failure and mortality. A holistic, integrated approach to AF management is recommended, which may include a focus on reducing risk factors and on medical management with anticoagulation and anti-arrhythmic drugs. There are also various ablation strategies that may be considered when anti-arrhythmic drugs fail to alleviate symptoms and reduce AF burden. These ablation techniques range from standalone percutaneous endocardial catheter ablation to open surgical ablation procedures concomitant with cardiac surgery. More recently, hybrid ablation that combines aspects of both surgical and electrophysiologically targeted ablation has been described. This article reviews the evolution of ablation strategies, beginning with the origin of the Cox maze IV procedure and continuing to the recent hybrid convergent approach, and provides a summary of the associated outcomes.

Ablation Therapy for Persistent Atrial Fibrillation.

Atrial Fibrillation (AF) is the most common form of electrical disturbance of the heart and contributes to significant patient morbidity and mortality. With a better understanding of the mechanisms of atrial fibrillation and improvements in mapping and ablation technologies, ablation has become a preferred therapy for patients with symptomatic AF. Pulmonary Vein Isolation (PVI) is the cornerstone for AF ablation therapy, but particularly in patients with AF occurring for longer than 7 days (persistent AF), identifying clinically significant nonpulmonary vein targets and achieving durability of ablation lesions remains an important challenge.

Cerebral Microbleeds With Atrial Fibrillation After Ablation Therapy.

BackgroundThe prevalence of cerebral microbleeds (CMBs) is significantly higher in patients with atrial fibrillation (AF) than in those without AF. CMBs in patients with AF have been reported to be primarily of the lobar type, but the exact cause of this remains unknown. We investigated the possibility that hemorrhagic transformation of embolic microinfarction can account for de novo lobar CMBs.MethodsA total of 101 patients who underwent ablation therapy for AF were prospectively registered, and 72 patients completed the assessment with MRI 6 months after catheter ablation. Brain MRI, including diffusion-weighted imaging (DWI) and susceptibility-weighted imaging (SWI), were examined at 1–3 days (baseline) and 6 months after catheter ablation. We quantitatively evaluated the spatial and temporal distribution of embolic microinfarctions and de novo CMBs.ResultsOf the 101 patients, 68 were enrolled in this study. Fifty-nine patients (86.8%) showed embolic microinfarctions on baseline DWI immediately after catheter ablation. There were 137 CMBs in SWI, and 96 CMBs were of the lobar type. Six months later, there were 208 CMBs, including 71 de novo CMBs, and 60 of 71 (84.5%) were of the lobar type. Of the 71 de novo CMBs, 56 (78.9%) corresponded to the location of previous embolic microinfarctions found on baseline DWI. The platelet count was significantly lower and hematocrit/hemoglobin and Fazekas score were higher in the group with de novo CMBs than in the group without de novo CMBs.ConclusionDe novo CMBs frequently appeared after catheter ablation therapy. Our results suggest that embolic microinfarction can cause lobar CMBs.

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability. Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, and 16 long-standing persistent), undergoing first ablation. Patients were followed for 1 year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fiber orientation maps, electrical properties, and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were postprocessed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging, and atrial fibrillation simulation metrics. We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging, and simulation stress tests (average 10-fold cross-validation area under the curve, 0.85±0.09; recall, 0.80±0.13; precision, 0.74±0.13) outperformed those trained to history and imaging (area under the curve, 0.66±0.17) or history alone (area under the curve, 0.61±0.14). A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalize selection for atrial fibrillation ablation.

Migraine and atrial fibrillation: a systematic review

Patients with migraine are at increased risk of stroke. The aim was to systematically review the current literature on the association between migraine and atrial fibrillation, which is a relevant risk factor for stroke. PubMed was searched for 'migraine' AND 'atrial fibrillation' and selected original investigations on the association of migraine and atrial fibrillation for our analysis. Articles without original data, such as guidelines, narrative reviews, editorials and others, were excluded. In all, 109 publications were found. Twenty-two were included and analysed for this review. The population-based Atherosclerosis Risk in Communities study showed a significant association of migraine with visual aura and incident atrial fibrillation (hazard ratio 1.30, 95% confidence interval 1.03-1.62, p = 0.02), but not for migraine without aura, compared to non-headache persons after multivariable adjustment for vascular risk factors. An even larger population-based study in Denmark confirmed this association (odds ratio 1.25, 95% confidence interval 1.16-1.36). Studies investigating patients with ischaemic stroke and migraine are methodologically insufficient and provide contradictory results. Ablation therapy for atrial fibrillation in patients with migraine might reduce migraine attacks, but transient post-ablation new-onset migraine-like headaches in persons without a history of migraine have also been reported. Population-based studies indicate a significant association of migraine with aura and atrial fibrillation. In practical terms, screening for atrial fibrillation in patients who have a long history of migraine might be reasonable, whereas in patients with stroke or other disorders and migraine extensive screening for atrial fibrillation should be performed as in all patients without migraine.

Reinforcement Learning to Improve Image-Guidance of Ablation Therapy for Atrial Fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia and currently affects more than 650,000 people in the United Kingdom alone. Catheter ablation (CA) is the only AF treatment with a long-term curative effect as it involves destroying arrhythmogenic tissue in the atria. However, its success rate is suboptimal, approximately 50% after a 2-year follow-up, and this high AF recurrence rate warrants significant improvements. Image-guidance of CA procedures have shown clinical promise, enabling the identification of key patient anatomical and pathological (such as fibrosis) features of atrial tissue, which require ablation. However, the latter approach still suffers from a lack of functional information and the need to interpret structures in the images by a clinician. Deep learning plays an increasingly important role in biomedicine, facilitating efficient diagnosis and treatment of clinical problems. This study applies deep reinforcement learning in combination with patient imaging (to provide structural information of the atria) and image-based modelling (to provide functional information) to design patient-specific CA strategies to guide clinicians and improve treatment success rates. To achieve this, patient-specific 2D left atrial (LA) models were derived from late-gadolinium enhancement (LGE) MRI scans of AF patients and were used to simulate patient-specific AF scenarios. Then a reinforcement Q-learning algorithm was created, where an ablating agent moved around the 2D LA, applying CA lesions to terminate AF and learning through feedback imposed by a reward policy. The agent achieved 84% success rate in terminating AF during training and 72% success rate in testing. Finally, AF recurrence rate was measured by attempting to re-initiate AF in the 2D atrial models after CA with 11% recurrence showing a great improvement on the existing therapies. Thus, reinforcement Q-learning algorithms can predict successful CA strategies from patient MRI data and help to improve the patient-specific guidance of CA therapy.