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

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...

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Veröffentlicht in:Research on biomedical engineering 2018-10, Vol.34 (4), p.337-349
Hauptverfasser: 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
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container_end_page 349
container_issue 4
container_start_page 337
container_title Research on biomedical engineering
container_volume 34
creator 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
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
doi_str_mv 10.1590/2446-4740.180040
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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&lt;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&lt;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.</description><identifier>ISSN: 2446-4732</identifier><identifier>ISSN: 2446-4740</identifier><identifier>EISSN: 2446-4740</identifier><identifier>DOI: 10.1590/2446-4740.180040</identifier><language>eng</language><publisher>Sociedade Brasileira de Engenharia Biomédica</publisher><subject>ENGINEERING, BIOMEDICAL</subject><ispartof>Research on biomedical engineering, 2018-10, Vol.34 (4), p.337-349</ispartof><rights>This work is licensed under a Creative Commons Attribution 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2390-cba53acbdfadea731e770760ff1903ddbd7da0e32720c0be71c12a9d9543b2783</citedby><cites>FETCH-LOGICAL-c2390-cba53acbdfadea731e770760ff1903ddbd7da0e32720c0be71c12a9d9543b2783</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids></links><search><creatorcontrib>Almeida, Tiago Paggi de</creatorcontrib><creatorcontrib>Schlindwein, Fernando Soares</creatorcontrib><creatorcontrib>Salinet, João</creatorcontrib><creatorcontrib>Li, Xin</creatorcontrib><creatorcontrib>Chu, Gavin Shen-Wei</creatorcontrib><creatorcontrib>Tuan, Jiun Haur</creatorcontrib><creatorcontrib>Stafford, Peter James</creatorcontrib><creatorcontrib>Ng, G André</creatorcontrib><creatorcontrib>Soriano, Diogo Coutinho</creatorcontrib><title>The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms</title><title>Research on biomedical engineering</title><addtitle>Res. Biomed. Eng</addtitle><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&lt;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&lt;0.0001). AEGs with 3 s or longer have shown ρ ≥ 80% for all variables. 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Biomed. Eng</addtitle><date>2018-10-01</date><risdate>2018</risdate><volume>34</volume><issue>4</issue><spage>337</spage><epage>349</epage><pages>337-349</pages><issn>2446-4732</issn><issn>2446-4740</issn><eissn>2446-4740</eissn><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&lt;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&lt;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.</abstract><pub>Sociedade Brasileira de Engenharia Biomédica</pub><doi>10.1590/2446-4740.180040</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record>
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title The temporal stability of recurrence quantification analysis attributes from chronic atrial fibrillation electrograms
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