Minimizing discordances in automated classification of fractionated electrograms in human persistent atrial fibrillation.

Ablation of persistent atrial fibrillation (persAF) targeting complex fractionated atrial electrograms (CFAEs) detected by automated algorithms has produced conflicting outcomes in previous electrophysiological studies. We hypothesize that the differences in these algorithms could lead to discordant...

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Publicado en:Medical & Biological Engineering & Computing Vol. 54; no. 11; pp. 1695 - 1707
Autores principales: Almeida, Tiago, Chu, Gavin, Salinet, João, Vanheusden, Frederique, Li, Xin, Tuan, Jiun, Stafford, Peter, Ng, G., Schlindwein, Fernando, Almeida, Tiago P, Chu, Gavin S, Salinet, João L, Vanheusden, Frederique J, Tuan, Jiun H, Stafford, Peter J, Ng, G André, Schlindwein, Fernando S
Formato: Journal Article
Publicado: Springer Nature Nov2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2016
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        atl: Minimizing discordances in automated classification of fractionated electrograms in human persistent atrial fibrillation.
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          Almeida, Tiago
          Chu, Gavin
          Salinet, João
          Vanheusden, Frederique
          Li, Xin
          Tuan, Jiun
          Stafford, Peter
          Ng, G.
          Schlindwein, Fernando
          Almeida, Tiago P
          Chu, Gavin S
          Salinet, João L
          Vanheusden, Frederique J
          Tuan, Jiun H
          Stafford, Peter J
          Ng, G André
          Schlindwein, Fernando S
        affil: Department of Engineering , University of Leicester , University Road Leicester LE1 7RH UK
      sug:
        subj:
          Atrial Fibrillation Diagnosis
          Algorithms
          Heart Function Tests
          Male
          Sensitivity and Specificity
          Middle Age
          Female
          Reproducibility of Results
          ROC Curve
          Aged
          Automation
          Scales
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: Ablation of persistent atrial fibrillation (persAF) targeting complex fractionated atrial electrograms (CFAEs) detected by automated algorithms has produced conflicting outcomes in previous electrophysiological studies. We hypothesize that the differences in these algorithms could lead to discordant CFAE classifications by the available mapping systems, giving rise to potential disparities in CFAE-guided ablation. This study reports the results of a head-to-head comparison of CFAE detection performed by NavX (St. Jude Medical) versus CARTO (Biosense Webster) on the same bipolar electrogram data (797 electrograms) from 18 persAF patients. We propose revised thresholds for both primary and complementary indices to minimize the differences in CFAE classification performed by either system. Using the default thresholds [NavX: CFE-Mean ≤ 120 ms; CARTO: ICL ≥ 7], NavX classified 70 % of the electrograms as CFAEs, while CARTO detected 36 % (Cohen's kappa κ ≈ 0.3, P < 0.0001). Using revised thresholds found using receiver operating characteristic curves [NavX: CFE-Mean ≤ 84 ms, CFE-SD ≤ 47 ms; CARTO: ICL ≥ 4, ACI ≤ 82 ms, SCI ≤ 58 ms], NavX classified 45 %, while CARTO detected 42 % (κ ≈ 0.5, P < 0.0001). Our results show that CFAE target identification is dependent on the system and thresholds used by the electrophysiological study. The thresholds found in this work counterbalance the differences in automated CFAE classification performed by each system. This could facilitate comparisons of CFAE ablation outcomes guided by either NavX or CARTO in future works.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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