Large left atrial appendage predicts the ablation outcome in hypertensive patients with atrial fibrillation

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Left Atrial Appendage Volume Predicts Atrial Fibrillation Recurrence after Radiofrequency Catheter Ablation: A Meta-Analysis

BACKGROUND

The influence of left atrial appendage volume (LAAV) on the recurrence of atrial fibrillation (AF) following radiofrequency catheter ablation remains unclear.

OBJECTIVES

We performed a meta-analysis to assess whether LAAV is an independent predictor of AF recurrence following radiofrequency catheter ablation.

METHODS

The PubMed and the Cochrane Library databases were searched until March 2022 to identify publications evaluating LAAV in association with AF recurrence after radiofrequency catheter ablation. Seven studies that fulfilled the specified criteria of our analysis were found. We used the Newcastle-Ottawa Scale to evaluate the quality of the studies. The pooled effects were evaluated depending on standardized mean differences (SMDs) or hazard ratios (HRs) with 95% confidence intervals (CIs). P values < 0.05 were considered statistically significant.

RESULTS

A total of 1017 patients from 7 cohort studies with a mean follow-up 16.3 months were included in the meta-analysis. Data from 6 studies (943 subjects) comparing LAAV showed that the baseline LAAV was significantly higher in patients with AF recurrence compared to those without AF (SMD: -0.63; 95% CI: -0.89 to -0,37; all p values < 0.05; I2= 62.6%). Moreover, higher LAAV was independently associated with a significantly higher risk of AF recurrence after radiofrequency catheter ablation (HR: 1.10; 95% CI: 1.02 to 1.18).

CONCLUSIONS

The meta-analysis showed that there is a significant correlation between LAAV and AF recurrence after radiofrequency catheter ablation, and the role of LAAV in AF patients should not be ignored in clinical practice.

Left atrial appendage function and structure predictors of recurrent atrial fibrillation after catheter ablation: A meta-analysis of observational studies

Background

The results of studies evaluating the left atrial appendage (LAA) function and structure as predictors of atrial fibrillation (AF) recurrence after catheter ablation (CA) are contradictory. Therefore, we performed a meta-analysis to assess whether the LAA function and structure can predict the recurrence of AF after CA.

Methods

The PubMed, EMBASE, Web of Science, and Cochrane library databases were used to conduct a comprehensive literature search. Finally, 37 studies encompassing 11 LAA parameters were included in this meta-analysis.

Results

Compared with those in the non-recurrence group, the recurrence group had increased LAA volume (SMD 0.53, 95% CI [0.36, 0.71] p < 0.00001), LAA volume index, LAA orifice area, and LAA orifice short/long axis and decreased LAA emptying flow velocity (SMD -0.54, 95% CI [-0.68, -0.40], P < 0.00001), LAA filling flow velocity, and LAA ejection fraction, while there was no significant difference in LAA morphology or LAA depth.

Conclusion

Large LAA structure of pre-ablation (LAA volume, orifice area, orifice long/short axis, and volume index) and decreased LAA function of pre-ablation (LAA emptying flow velocity, filling flow velocity, ejection fraction, and LASEC) increase the odds of AF recurrence after CA.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022324533].

Atrial fibrillation ablation: the position of computed tomography in pre-procedural imaging

Atrial fibrillation (AF) is the most common supraventricular arrhythmia. Despite significant advances in its treatment, it still remains one of the leading causes of cardiovascular morbidity and mortality. In the last two decades, pulmonary vein isolation (PVI) was developed as the most effective treatment option. The reported effectiveness of a single ablation procedure ranges from 40% to 69% with single, and up to 88% with repeated procedures, with acceptable safety profile. The PubMed database was searched, using terms including ‘atrial fibrillation ablation’, ‘pulmonary vein isolation’, ‘computed tomography’, ‘pulmonary vein anatomy’ and ‘ovality index’. Papers were reviewed for relevance and scientific merit. Different imaging techniques are used for pre-procedural assessment of left atrial (LA) anatomy, of which computed tomography (CT) is the most common. It allows assessing pulmonary vein (PV) anatomy, the LA wall thickness in different regions and the left atrial appendage (LAA) anatomy, together with excluding the presence of intracardiac thrombi. Pre-procedural PVs imaging is important regardless of the selected ablation technique, however, cryoballoon (CB) ablation seems to be particularly anatomy-dependent. Additionally, CT also permits assessment of several PVs characteristics (geometry, dimensions, angulations, the ostium area, orientation and ovality index (OI), which are essential for the patients’ qualification and designing the strategy of AF ablation. In this paper, we have reviewed the role of CT imaging in patients undergoing ablation procedure due to recurrent/symptomatic atrial fibrillation. Moreover, we discussed the relevant literature.

Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity

Parkinson's disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the Brain Cerebellum were also recognized to confer major PD risk. These findings were replicated in two additional, independent cohorts (the UK Biobank, and NeuroX) and thus warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.