The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , , , |
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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Research on Biomedical Engineering (Online) |
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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 |
_version_ |
1752126288964878336 |