A nomogram based on CHADS2 score for predicting atrial fibrillation recurrence after cryoballoon ablation

Association between preablation and postablation neutrophil-lymphocyte ratio and atrial fibrillation recurrence: A meta-analysis

Atrial fibrillation (AF) recurrence has become common in patients who have undergone catheter ablation. High neutrophil lymphocyte ratios (NLR) have been linked to an increased risk of recurrent AF. The research is, however, not conclusive. This meta-analysis addressed the value of easily accessible and affordable pre- and postablation NLR levels as indicators of AF recurrence in patients who had undergone ablation. We searched PubMed, SCOPUS, and Google Scholar for pertinent studies through May 2023. Using random effects models, the aggregated odds ratio (OR) of pre- and post-NLR and AF recurrence was estimated. Inter-study heterogeneity was described using I 2 statistics and leave-one-out sensitivity analysis. A p-value < .05 was considered statistically significant. The literature search yielded 270 studies, seven of which were included in this meta-analysis of 1923 patients who experienced AF recurrence after undergoing ablation. There are five retrospective and two prospective studies with a mean follow-up of 20.5 months. The unadjusted odds ratio (OR) of AF recurrence for preablation NLR was 1.33 (95% CI: 1.04-1.71, p < .01, I 2 = 95.49%), while the adjusted OR was 1.45 (95% CI: 0.87-2.43, p < .01, I 2 = 95.1%). The unadjusted odds ratio (OR) for postablation NLR was 1.21 (95% CI: 1.09-1.36, p < .01, I 2 = 85.9%), and the adjusted odds ratio (OR) was 1.28 (95% CI: 0.93-1.76), demonstrating significant heterogeneity (I 2 = 95.32%) with a p-value < .01. NLR was significantly associated with AF recurrence prediction. To detect AF recurrence, we recommend that clinicians add a simple NLR blood test to their diagnostic modalities.

Novel scoring system derived from meta-analysis and validated in cohort population for predicting 1-year atrial fibrillation recurrence after cryoballoon catheter ablation: The HeLPS-Cryo score

BACKGROUND

Atrial fibrillation (AF) recurrence rates in 1 year after cryoballoon ablation catheter (CBCA) are still high. We purposed to identify strong predictors for AF recurrence after the successful CBCA procedure and develop a new scoring system based only on pre-procedural parameters.

METHODS

In the derivation phase, a systematic review and meta-analysis identified the strong predictors of AF recurrence after the CBCA. The pooled hazard ratio (HR) was used to create the new scoring system. The second phase validated the new scoring system in the cohort population.

RESULTS

A meta-analysis including 29 cohort studies with 16196 participants confirmed that persistent AF, stroke, heart failure, and left atrial diameter (LAD) >40 mm were powerful predictors for AF recurrence after the CBCA procedure. The HeLPS-Cryo (heart failure [1], left atrial dilatation [1], persistent AF [2], and stroke [2]) was developed based on those pre-procedural predictors. It was validated in 140 patients receiving CBCA procedures and revealed excellent predictive performance for 1-year AF recurrence (AUC = 0.8877; 95% CI = 0.8208 to 0.9546). The HeLPS-Cryo score of ≥3 could predict 1-year AF recurrence with sensitivity and specificity of 78.9% and 87.9%, respectively. The positive predictive value was 66.7%, and the negative predictive value was 93.1%.

CONCLUSION

The HeLPS-Cryo score can help the physician estimate the probability of 1-year AF recurrence after the successful CBCA procedure. Patients with HeLPS-Cryo score <3 are good candidates for the CBCA procedure.

Association between the Albumin-to-Globulin Ratio and Atrial Fibrillation in Patients with Hypertrophic Cardiomyopathy

Background

Atrial fibrillation (AF), which occurs four to six times more frequently in hypertrophic cardiomyopathy (HCM) patients than in the general population, is the most common persistent arrhythmia and has a substantial therapeutic consequence. In HCM patients, there are currently no discovered signs that could be utilized to identify AF.

Methods

From 2018 to 2022, 493 individuals with a continuous diagnosis of HCM were examined at Beijing Anzhen Hospital. AF was proven using routine electrocardiography (ECG), 24-hour Holter ECGs, or bedside ECGs. Echocardiography and blood tests were performed for all patients. Analysis and comparison of the traits were performed in HCM patients with AF (n = 77) and without AF (n = 416).

Results

Age (p < 0.001), prevalence of ventricular tachycardia (VT, p < 0.001), prevalence of pulmonary artery hypertension (p = 0.027), and albumin-to-globulin ratio (AGR, p = 0.046) were all significantly higher in patients with AF, compared to patients without AF. In multivariate logistic analysis, age (odds ratio [OR], 1.063; 95% confidence interval [CI], 1.032-1.095; p < 0.001), history of VT (OR, 2.702; 95% CI, 1.007-7.255; p = 0.048), AGR (OR, 3.477; 95% CI, 1.417-8.536; p = 0.007), left atrial diameter (OR, 1.132; 95% CI, 1.073-1.194; p < 0.001), left ventricular end-diastolic diameter (OR, 0.861; 95% CI, 0.762-0.974; p = 0.017), left ventricular end-systolic diameter (OR, 1.239; 95% CI, 1.083-1.417; p = 0.002), and peak A wave velocity (OR, 0.983; 95% CI, 0.972-0.994; p = 0.002) were independently associated with AF in HCM patients. In the receiver operating characteristic curve analysis, the area under the curve for the established model was 0.819 (95% CI, 0.755-0.883, p = 0.033), with a sensitivity and specificity of 0.763 and 0.816, respectively, for AF occurrence in HCM patients.

Conclusions

In individuals with HCM, a history of VT and a higher AGR are independently linked to AF. Further investigation is necessary to determine whether increased AGR represents a risk factor for embolic stroke or cardiovascular death.

Red cell distribution width to albumin ratio is a risk factor for atrial fibrillation in subjects hospitalized with coronary angiography

BACKGROUND

Red cell distribution width to albumin ratio (RAR) has been demonstrated to be associated with the risk of cardiovascular diseases. However, it is still unknown whether the RAR affects atrial fibrillation (AF). Therefore, this study aimed to investigate the association between RAR and AF in subjects hospitalized with coronary angiography.

METHODS

A total of 2436 participants were retrospectively included. Red cell distribution width, albumin and other data were collected. AF was confirmed using 12-lead electrocardiogram (ECG) or 24-h Holter. All participants were divided into four groups according to the RAR values by quartile (Q1, Q2, Q3, Q4). Univariate and multivariate logistic regression were performed to examine the correlation between RAR and AF.

RESULTS

Among the 2436 participants, 227 (9.3%) AF cases were observed. The RDW and RAR were significantly higher in AF group than in non-AF group (all P < 0.001). Univariate logistic regression showed an positive association between RAR and AF (P < 0.001). In multivariate logistic regression, RAR was found to be an independent risk factor of AF after adjusting for confounding factors (OR:2.015, 95%CI:1.315-3.089, P = 0.001).

CONCLUSIONS

The present study indicated that elevated RAR level was independently correlated with increased risk of AF in subjects hospitalized with coronary angiography.

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.