3.8 Proceedings Paper

Optimizing Atrial Electrogram Classification Based on Local Ablation Outcome in Human Atrial Fibrillation

期刊

2020 COMPUTING IN CARDIOLOGY
卷 -, 期 -, 页码 -

出版社

IEEE
DOI: 10.22489/CinC.2020.131

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资金

  1. NIHR Leicester Biomedical Research Centre
  2. FAPESP [2019/051921, 2019/09512-0]
  3. Medical Research Council UK (MRC DPFS) [MR/S037306/1]
  4. Fondazione Cassa di Risparmio di Trento e Rovereto [2016.0273]
  5. Sao Paulo Research Foundation (FAPESP, Brazil) [2017/00319-8, 2018/02251-4]
  6. British Heart Foundation (BHF) [PG/18/33/33780]
  7. BHF Research Accelerator for Early Career Researcher

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Changes in atrial fibrillation cycle length (AF-CL) are broadly used as a 'ground truth' to assess the effect of substrate modification during AF ablation. This work sought to optimize thresholds for changes in coronary sinus CL (CS-CL) after local ablation using different atrial electrogram (AEG)-derived markers. 834 AEGs were collected from 11 patients undergoing persAF ablation. CS-CL was measured before and after each ablation point. Five AEG-derived markers were tested as classifiers for CS-CL changes: ICL (Biosense Webster), CFE-Mean (St. Jude Medical), Wave Similarity, Shannon Entropy and AEG-CL. The area under the receiver operating characteristic (AUROC) curve was used to assess the quality of classification for each marker. Maximum AUROC was found at threshold values between 9 and 14 ms in all markers, except for Shannon Entropy. The average AUROC of the five markers reached a maximum of 0.60 at a threshold value of 10 ms. The 10 ms threshold is suggested as a starting setpoint for future studies seeking to identify AF ablation targets based on an objective 'ground truth'.

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