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Atrial Periodic Source Spectrum From Preoperative Body Surface Potentials Predicts Long-Term Recurrence of Atrial Fibrillation.
IEEE Trans Biomed Eng ; 70(7): 2131-2138, 2023 07.
Article in En | MEDLINE | ID: mdl-37018681
ABSTRACT

OBJECTIVE:

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.

METHODS:

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.

RESULTS:

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 ). CONCLUSION AND

SIGNIFICANCE:

Preoperative BSPs demonstrate effective prediction in the long-term outcomes, highlighting their potential for patient screening in AF ablation therapy.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Atrial Fibrillation / Catheter Ablation Type of study: Clinical_trials / Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: IEEE Trans Biomed Eng Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Atrial Fibrillation / Catheter Ablation Type of study: Clinical_trials / Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: IEEE Trans Biomed Eng Year: 2023 Document type: Article