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The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
Almeida, Tiago Paggi de; Schlindwein, Fernando Soares; Salinet, João; Li, Xin; Chu, Gavin Shen-Wei; Tuan, Jiun Haur; Stafford, Peter James; Ng, G André; Soriano, Diogo Coutinho.
  • Almeida, Tiago Paggi de; Aeronautics Institute of Technology. São José dos Campos. BR
  • Schlindwein, Fernando Soares; University of Leicester. Department of Engineering. Leicester. GB
  • Salinet, João; Federal ABC University. Engineering, Modelling and Applied Social Sciences Centre. São Bernardo do Campo. BR
  • Li, Xin; University of Leicester. Department of Cardiovascular Sciences. Leicester. GB
  • Chu, Gavin Shen-Wei; University of Leicester. Department of Cardiovascular Sciences. Leicester. GB
  • Tuan, Jiun Haur; University Hospitals of Leicester NHS Trust. Leicester. GB
  • Stafford, Peter James; University Hospitals of Leicester NHS Trust. Leicester. GB
  • Ng, G André; Glenfield Hospital. National Institute for Health Research Leicester Cardiovascular Biomedical Research Centre. Leicester. GB
  • Soriano, Diogo Coutinho; Federal ABC University. Engineering, Modelling and Applied Social Sciences Centre. São Bernardo do Campo. BR
Res. Biomed. Eng. (Online) ; 34(4): 337-349, Oct.-Dec. 2018. tab, graf
Artigo em Inglês | LILACS | ID: biblio-984963
ABSTRACT
Abstract Introduction The temporal behavior of atrial electrograms (AEGs) collected during persistent atrial fibrillation (persAF) directly affects ablative treatment outcomes. We investigated different durations of AEGs collected during persAF using recurrence quantification analysis (RQA). Methods 797 bipolar AEGs with different durations (from 0.5 s to 8 s) from 18 patients were investigated. Four RQA-based attributes were evaluated based on AEG durations determinism (DET); recurrence rate (RR); laminarity (LAM); and diagonal lines' entropy (ENTR). The Spearman correlation (ρ) between each duration versus 8 s was calculated. AEG classification was performed following the CARTO criteria (Biosense Webster) and receiving operating characteristic (ROC) curves were created for the RQA variables. Results The RQA variables successfully discriminated the AEGs the area under the ROC curves were as high as 0.70 for AEGs with 3.5 s or greater. Three types of AEGs were found using these variables normal, fractionated and temporally unstable. The number of unstable AEGs decreased with longer AEG segments. Different AEG durations significantly affected the RQA variables (P<0.0001), with no statistical difference between the durations 6 s, 7 s and 8 s for DET, LAM and ENTR, and no difference between 7 s and 8 s for RR (P<0.0001). AEGs with 3 s or longer have shown ρ ≥ 80% for all variables. Conclusion The RQA variables have been shown effective in the characterization of AEGs collected during persAF with a shorter duration than current recommendations, which motivates their use for the characterization of atrial substrate during persAF ablation.


Texto completo: DisponíveL Índice: LILACS (Américas) Tipo de estudo: Guia de Prática Clínica Idioma: Inglês Revista: Res. Biomed. Eng. (Online) Assunto da revista: Engenharia Biom‚dica Ano de publicação: 2018 Tipo de documento: Artigo / Documento de projeto País de afiliação: Brasil / Reino Unido Instituição/País de afiliação: Aeronautics Institute of Technology/BR / Federal ABC University/BR / Glenfield Hospital/GB / University Hospitals of Leicester NHS Trust/GB / University of Leicester/GB

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Texto completo: DisponíveL Índice: LILACS (Américas) Tipo de estudo: Guia de Prática Clínica Idioma: Inglês Revista: Res. Biomed. Eng. (Online) Assunto da revista: Engenharia Biom‚dica Ano de publicação: 2018 Tipo de documento: Artigo / Documento de projeto País de afiliação: Brasil / Reino Unido Instituição/País de afiliação: Aeronautics Institute of Technology/BR / Federal ABC University/BR / Glenfield Hospital/GB / University Hospitals of Leicester NHS Trust/GB / University of Leicester/GB