The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms

Detalhes bibliográficos
Autor(a) principal: Almeida,Tiago Paggi de
Data de Publicação: 2018
Outros Autores: Schlindwein,Fernando Soares, Salinet,João, Li,Xin, Chu,Gavin Shen-Wei, Tuan,Jiun Haur, Stafford,Peter James, Ng,G André, Soriano,Diogo Coutinho
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research on Biomedical Engineering (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402018000400337
Resumo: 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.
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spelling The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrogramsPersistent atrial fibrillationFractionated electrogramsCatheter ablationElectrophysiology mappingRecurrence plotsRecurrence quantification analysisAbstract 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.Sociedade Brasileira de Engenharia Biomédica2018-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402018000400337Research on Biomedical Engineering v.34 n.4 2018reponame:Research on Biomedical Engineering (Online)instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)instacron:SBEB10.1590/2446-4740.180040info:eu-repo/semantics/openAccessAlmeida,Tiago Paggi deSchlindwein,Fernando SoaresSalinet,JoãoLi,XinChu,Gavin Shen-WeiTuan,Jiun HaurStafford,Peter JamesNg,G AndréSoriano,Diogo Coutinhoeng2019-01-21T00:00:00Zoai:scielo:S2446-47402018000400337Revistahttp://www.rbejournal.org/https://old.scielo.br/oai/scielo-oai.php||rbe@rbejournal.org2446-47402446-4732opendoar:2019-01-21T00:00Research on Biomedical Engineering (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)false
dc.title.none.fl_str_mv The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
title The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
spellingShingle The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
Almeida,Tiago Paggi de
Persistent atrial fibrillation
Fractionated electrograms
Catheter ablation
Electrophysiology mapping
Recurrence plots
Recurrence quantification analysis
title_short The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
title_full The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
title_fullStr The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
title_full_unstemmed The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
title_sort The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
author Almeida,Tiago Paggi de
author_facet 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
author_role author
author2 Schlindwein,Fernando Soares
Salinet,João
Li,Xin
Chu,Gavin Shen-Wei
Tuan,Jiun Haur
Stafford,Peter James
Ng,G André
Soriano,Diogo Coutinho
author2_role author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv 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
dc.subject.por.fl_str_mv Persistent atrial fibrillation
Fractionated electrograms
Catheter ablation
Electrophysiology mapping
Recurrence plots
Recurrence quantification analysis
topic Persistent atrial fibrillation
Fractionated electrograms
Catheter ablation
Electrophysiology mapping
Recurrence plots
Recurrence quantification analysis
description 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.
publishDate 2018
dc.date.none.fl_str_mv 2018-10-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402018000400337
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402018000400337
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2446-4740.180040
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Engenharia Biomédica
publisher.none.fl_str_mv Sociedade Brasileira de Engenharia Biomédica
dc.source.none.fl_str_mv Research on Biomedical Engineering v.34 n.4 2018
reponame:Research on Biomedical Engineering (Online)
instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)
instacron:SBEB
instname_str Sociedade Brasileira de Engenharia Biomédica (SBEB)
instacron_str SBEB
institution SBEB
reponame_str Research on Biomedical Engineering (Online)
collection Research on Biomedical Engineering (Online)
repository.name.fl_str_mv Research on Biomedical Engineering (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)
repository.mail.fl_str_mv ||rbe@rbejournal.org
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