English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia often treatedconcomitantly with other cardiac interventions through the Cox Maze procedure.This highly invasive intervention is still linked to a long-term recurrencerate of approximately 35% in permanent AF patients. The aim of this study is topreoperatively predict long-term AF recurrence post-surgery through theanalysis of atrial activity (AA) organization from non-invasiveelectrocardiographic (ECG) recordings. A dataset comprising ECGs from 53patients with permanent AF who had undergone Cox Maze concomitant surgery wasanalyzed. The AA was extracted from the lead V1 of these recordings and thencharacterized using novel predictors, such as the mean and standard deviationof the relative wavelet energy (RWEm and RWEs) across different scales, and anentropy-based metric that computes the stationary wavelet entropy variability(SWEnV). The individual predictors exhibited limited predictive capabilities toanticipate the outcome of the procedure, with the SWEnV yielding aclassification accuracy (Acc) of 68.07%. However, the assessment of the RWEsfor the seventh scale (RWEs7), which encompassed frequencies associated withthe AA, stood out as the most promising individual predictor, with sensitivity(Se) and specificity (Sp) values of 80.83% and 67.09%, respectively, and an Accof almost 75%. Diverse multivariate decision tree-based models were constructedfor prediction, giving priority to simplicity in the interpretation of theforecasting methodology. In fact, the combination of the SWEnV and RWEs7consistently outperformed the individual predictors and excelled in predictingpost-surgery outcomes one year after the Cox Maze procedure, with Se, Sp, andAcc values of approximately 80%, thus surpassing the results of previousstudies based on anatomical predictors associated with atrial function orclinical data.

entropy

Novel Entropy-Based Metrics for Long-Term Atrial Fibrillation Recurrence  Prediction Following Surgical Ablation: Insights from Preoperative  Electrocardiographic Analysis