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

Predictive Value of Machine Learning for Recurrence of Atrial Fibrillation after Catheter Ablation: A Systematic Review and Meta-Analysis

Background

Accurate detection of atrial fibrillation (AF) recurrence after catheter ablation is crucial. In this study, we aimed to conduct a systematic review of machine-learning-based recurrence detection in the relevant literature.

Methods

We conducted a comprehensive search of PubMed, Embase, Cochrane, and Web of Science databases from 1980 to December 31, 2022 to identify studies on prediction models for AF recurrence risk after catheter ablation. We used the prediction model risk of bias assessment tool (PROBAST) to assess the risk of bias, and R4.2.0 for meta-analysis, with subgroup analysis based on model type.

Results

After screening, 40 papers were eligible for synthesis. The pooled concordance index (C-index) in the training set was 0.760 (95% confidence interval [CI] 0.739 to 0.781), the sensitivity was 0.74 (95% CI 0.69 to 0.77), and the specificity was 0.76 (95% CI 0.72 to 0.80). The combined C-index in the validation set was 0.787 (95% CI 0.752 to 0.821), the sensitivity was 0.78 (95% CI 0.73 to 0.83), and the specificity was 0.75 (95% CI 0.65 to 0.82). The subgroup analysis revealed no significant difference in the pooled C-index between models constructed based on radiomics features and those based on clinical characteristics. However, radiomics based showed a slightly higher sensitivity (training set: 0.82 vs. 0.71, validation set: 0.83 vs. 0.73). Logistic regression, one of the most common machine learning (ML) methods, exhibited an overall pooled C-index of 0.785 and 0.804 in the training and validation sets, respectively. The Convolutional Neural Networks (CNN) models outperformed these results with an overall pooled C-index of 0.862 and 0.861. Age, radiomics features, left atrial diameter, AF type, and AF duration were identified as the key modeling variables.

Conclusions

ML has demonstrated excellent performance in predicting AF recurrence after catheter ablation. Logistic regression (LR) being the most widely used ML algorithm for predicting AF recurrence, also showed high accuracy. The development of risk prediction nomograms for wide application is warranted.

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

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

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.

A prediction model based on functional mitral regurgitation for the recurrence of paroxysmal atrial fibrillation (PAF) after post-circular pulmonary vein radiofrequency ablation (CPVA)

AIM

To construct a prediction model based on functional mitral regurgitation (FMR) in patients with paroxysmal atrial fibrillation (PAF) to predict atrial fibrillation recurrence after the post-circular pulmonary vein radiofrequency ablation (CPVA).

METHODS

We retrospectively analyzed 289 patients with PAF who underwent CPVA for the first time. The patients were randomly divided into modeling group and verification group at the ratio of 75:25. In the modeling group, the multivariate logistic regression was used to analyze and construct a prediction model for post-CPVA recurrence in PAF patients, which was then validated in the verification group.

RESULTS

(1) After 3-6 months of follow-up, the patients were divided into sinus rhythm group (252 cases) and recurrence group (24 cases); (2) In the modeling group, the age, left atrial diameter (LAD), and the degree of MR (mild, moderate, severe) were higher in recurrence group than that of the sinus rhythm group, and the left atrial appendage emptying velocity (LAAV) was lower in recurrence group (all p < .05). (3) A model for predicting the recurrence of PAF after radiofrequency ablation was constructed in the modeling group. The equation was: Logit(P) = -3.253 + .092 × age + 1.263 × mild MR + 2.325 × moderate MR + 5.111 × severe MR -.113 × LAAV. The area under the curve (AUC) of the model was .889 in modeling group and .866 in verification group, and the difference was not statistically significant (p > .05).

CONCLUSION

The prediction model of atrial fibrillation (AF) recurrence after CPVA in PAF patients has good predictive efficacy, specificity, and accuracy.

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].

Left atrial appendage flow velocity predicts recurrence of atrial fibrillation after catheter ablation: A systematic review and meta-analysis

Purpose

There is increasing evidence that left atrial appendage flow velocity (LAAFV) is linked to the recurrence of atrial fibrillation (AF) after catheter ablation (CA), suggesting the potential predictable significance of LAAFV in this setting. We performed a systematic review and meta-analysis to assess whether LAAFV is association with AF recurrence after CA.

Methods

Up to May 1, 2022, six databases (PubMed, EMBASE, Web of Science, Cochrane Library, Scopus, and CINAHL) were searched for literature reporting the association between LAAFV and AF recurrence after CA. All statistical analyses were carried out using STATA version 16 software. Heterogeneity was determined by the Cochrane’s Q test and I² statistics. The Newcastle-Ottawa Scale (NOS) was used to assess the methodological quality of each included study, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was adopted to evaluate the quality of evidence.

Result

Sixteen studies with 5,006 AF patients after CA (1,479 patients with AF recurrence, 3,527 without AF recurrence) were included in the meta-analysis. The meta-analysis of 15 studies (16 data sets) showed that patients with recurrence exhibited lower LAAFV values than those without recurrence [standardized mean difference (SMD): −0.65, 95% CI: −0.88 to −0.42, P < 0.01]. Moreover, we evaluated the association of LAAFV and the risk of AF recurrence after CA. Nine studies (11 data sets) defined LAAFV as continuous variables, and the pooled analysis suggested that for every 1 cm/s rise in LAAFV values, the risk of AF recurrence after CA decreased by 3% [Odds Ratio (OR): 0.97, 95% CI: 0.95 to 0.99, P < 0.01]. Seven studies defined LAAFV as categorical variables, and the pooled analysis showed that lower LAAFV were associated with an increased risk of AF recurrence after CA [OR: 2.28, 95% CI: 1.46 to 3.57, P < 0.01]. The subgroup analyses showed that the association between LAAFV and AF recurrence after CA was not significantly affected by the AF type and ablation procedure. The NOS indicated that included studies were moderate to high quality, while the GRADE assessment suggested a low certainty of the evidence.

Conclusion

Lower LAAFV may be associated with an increased risk of AF recurrence after CA. Further studies with well designed and randomized studies for LAAFV should be conducted.

Systematic review registration

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022333627].

Assessment of Left Atrial Structure and Function by Echocardiography in Atrial Fibrillation

Atrial fibrillation (AF) is the most common arrhythmia with significant morbidity and mortality. Exacerbated by the aging population, the prevalence of AF is gradually increasing. Accurate evaluation of structure and function of left atrium (LA) has important prognostic significance in patients with AF. Echocardiography is the imaging technique of first choice to assess LA structure and function due to its better availability, accessibility and safety over cardiac computed tomography and cardiac magnetic resonance. Therefore, the aim of this review is to summarize the recent research progress of evaluating LA size by three-dimensional echocardiography and LA function by speckle tracking echocardiography (STE) in predicting the occurrence and recurrence of AF and determining the risk of stroke in AF. In addition, we summarized the role of traditional echocardiography in detecting AF patients that are at high risk of heart failure or cardiovascular death.