T-Wave Morphology Analysis in Congenital Long QT Syndrome Discriminates Patients From Healthy Individuals
Abstract Objectives This study aims to assess the capability of T-wave analysis to: 1) identify genotype-positive long QT syndrome (LQTS) patients; 2) identify LQTS patients with borderline or normal QTc interval (≤460 ms); and 3) classify LQTS subtype. Background LQTS often presents with a nondiagn...
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| Veröffentlicht in: | JACC. Clinical electrophysiology 2017-04, Vol.3 (4), p.374-381 |
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| creator | Porta-Sánchez, Andreu, MD Spillane, David R., MSc, MDCM(c) Harris, Louise, MD Xue, Joel, PhD Dorsey, Pat, BS Care, Melanie, MSc Chauhan, Vijay, MD Gollob, Michael H., MD Spears, Danna A., MD |
| description | Abstract Objectives This study aims to assess the capability of T-wave analysis to: 1) identify genotype-positive long QT syndrome (LQTS) patients; 2) identify LQTS patients with borderline or normal QTc interval (≤460 ms); and 3) classify LQTS subtype. Background LQTS often presents with a nondiagnostic electrocardiogram (ECG). T-wave abnormalities may be the only marker of this potentially lethal arrhythmia syndrome. Methods ECGs taken at rest in 108 patients (43 with LQTS1, 20 with LQTS2, and 45 control subjects) were evaluated for T-wave flatness, asymmetry, and notching, which produces a morphology combination score (MCS) of the 3 features (MCS = 1.6 × flatness + asymmetry + notch) using QT Guard Plus Software (GE Healthcare, Milwaukee, Wisconsin). To assess for heterogeneity of repolarization, the principal component analysis ratio 2 (PCA-2) was calculated. Results Mean QTc intervals were 486 ± 50 ms (LQTS1), 479 ± 36 ms (LQTS2), and 418 ± 24 ms (control subjects) (p < 0.05). MCS and PCA-2 differed between LQTS patients and control subjects (MCS: 117.8 ± 57.4 vs. 71.9 ± 16.2; p |
| doi_str_mv | 10.1016/j.jacep.2016.10.013 |
| format | Article |
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Background LQTS often presents with a nondiagnostic electrocardiogram (ECG). T-wave abnormalities may be the only marker of this potentially lethal arrhythmia syndrome. Methods ECGs taken at rest in 108 patients (43 with LQTS1, 20 with LQTS2, and 45 control subjects) were evaluated for T-wave flatness, asymmetry, and notching, which produces a morphology combination score (MCS) of the 3 features (MCS = 1.6 × flatness + asymmetry + notch) using QT Guard Plus Software (GE Healthcare, Milwaukee, Wisconsin). To assess for heterogeneity of repolarization, the principal component analysis ratio 2 (PCA-2) was calculated. Results Mean QTc intervals were 486 ± 50 ms (LQTS1), 479 ± 36 ms (LQTS2), and 418 ± 24 ms (control subjects) (p < 0.05). MCS and PCA-2 differed between LQTS patients and control subjects (MCS: 117.8 ± 57.4 vs. 71.9 ± 16.2; p < 0.001; PCA-2: 20.2 ± 10.4% vs. 14.6 ± 5.5%; p < 0.001), LQTS1 and LQTS2 patients (MCS: 96.3 ± 28.7 vs. 164 ± 75.2; p < 0.001; PCA-2: 17.8 ± 8.3% vs. 25 ± 12.6%; p < 0.001), and between LQTS patients with borderline or normal QTc intervals (n = 17) and control subjects (MCS: 105.7 ± 49.9 vs. 71.9 ± 16.2; p < 0.001; PCA-2: 18.1 ± 7.2% vs. 14.6 ± 5.5%; p < 0.001). T-wave metrics were consistent across multiple ECGs from individual patients based on the average intraclass correlation coefficient (MCS: 0.96; PCA-2: 0.86). Conclusions Automated T-wave morphology analysis accurately discriminates patients with pathogenic LQTS mutations from control subjects and between the 2 most common LQTS subtypes. Mutation carriers without baseline QTc prolongation were also identified. This may be a useful tool for screening families of LQTS patients, particularly when the QTc interval is subthreshold and genetic testing is unavailable.]]></description><identifier>ISSN: 2405-500X</identifier><identifier>EISSN: 2405-5018</identifier><identifier>DOI: 10.1016/j.jacep.2016.10.013</identifier><identifier>PMID: 29759450</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Cardiovascular ; long QT syndrome ; morphology combination score ; principal component analysis ; T-wave</subject><ispartof>JACC. Clinical electrophysiology, 2017-04, Vol.3 (4), p.374-381</ispartof><rights>American College of Cardiology Foundation</rights><rights>2017 American College of Cardiology Foundation</rights><rights>Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c329t-777a16b36b7740596a5fa3949154888820866255283a6058aa7ec0826ce333cb3</citedby><cites>FETCH-LOGICAL-c329t-777a16b36b7740596a5fa3949154888820866255283a6058aa7ec0826ce333cb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29759450$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Porta-Sánchez, Andreu, MD</creatorcontrib><creatorcontrib>Spillane, David R., MSc, MDCM(c)</creatorcontrib><creatorcontrib>Harris, Louise, MD</creatorcontrib><creatorcontrib>Xue, Joel, PhD</creatorcontrib><creatorcontrib>Dorsey, Pat, BS</creatorcontrib><creatorcontrib>Care, Melanie, MSc</creatorcontrib><creatorcontrib>Chauhan, Vijay, MD</creatorcontrib><creatorcontrib>Gollob, Michael H., MD</creatorcontrib><creatorcontrib>Spears, Danna A., MD</creatorcontrib><title>T-Wave Morphology Analysis in Congenital Long QT Syndrome Discriminates Patients From Healthy Individuals</title><title>JACC. Clinical electrophysiology</title><addtitle>JACC Clin Electrophysiol</addtitle><description><![CDATA[Abstract Objectives This study aims to assess the capability of T-wave analysis to: 1) identify genotype-positive long QT syndrome (LQTS) patients; 2) identify LQTS patients with borderline or normal QTc interval (≤460 ms); and 3) classify LQTS subtype. Background LQTS often presents with a nondiagnostic electrocardiogram (ECG). T-wave abnormalities may be the only marker of this potentially lethal arrhythmia syndrome. Methods ECGs taken at rest in 108 patients (43 with LQTS1, 20 with LQTS2, and 45 control subjects) were evaluated for T-wave flatness, asymmetry, and notching, which produces a morphology combination score (MCS) of the 3 features (MCS = 1.6 × flatness + asymmetry + notch) using QT Guard Plus Software (GE Healthcare, Milwaukee, Wisconsin). To assess for heterogeneity of repolarization, the principal component analysis ratio 2 (PCA-2) was calculated. Results Mean QTc intervals were 486 ± 50 ms (LQTS1), 479 ± 36 ms (LQTS2), and 418 ± 24 ms (control subjects) (p < 0.05). MCS and PCA-2 differed between LQTS patients and control subjects (MCS: 117.8 ± 57.4 vs. 71.9 ± 16.2; p < 0.001; PCA-2: 20.2 ± 10.4% vs. 14.6 ± 5.5%; p < 0.001), LQTS1 and LQTS2 patients (MCS: 96.3 ± 28.7 vs. 164 ± 75.2; p < 0.001; PCA-2: 17.8 ± 8.3% vs. 25 ± 12.6%; p < 0.001), and between LQTS patients with borderline or normal QTc intervals (n = 17) and control subjects (MCS: 105.7 ± 49.9 vs. 71.9 ± 16.2; p < 0.001; PCA-2: 18.1 ± 7.2% vs. 14.6 ± 5.5%; p < 0.001). T-wave metrics were consistent across multiple ECGs from individual patients based on the average intraclass correlation coefficient (MCS: 0.96; PCA-2: 0.86). Conclusions Automated T-wave morphology analysis accurately discriminates patients with pathogenic LQTS mutations from control subjects and between the 2 most common LQTS subtypes. Mutation carriers without baseline QTc prolongation were also identified. This may be a useful tool for screening families of LQTS patients, particularly when the QTc interval is subthreshold and genetic testing is unavailable.]]></description><subject>Cardiovascular</subject><subject>long QT syndrome</subject><subject>morphology combination score</subject><subject>principal component analysis</subject><subject>T-wave</subject><issn>2405-500X</issn><issn>2405-5018</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFUU1v1DAQtRAVrUp_ARLykUsWf8ROcgCpWiittKigLoKb5XVmW6dee2snK-Xf9Lf0l9Xplh644MuMx-_N-L1B6B0lM0qo_NjNOm1gO2P5kiszQvkrdMRKIgpBaP36JSd_DtFJSh0hhApWM1q-QYesqURTCnKEbpfFb70D_D3E7U1w4XrEp167MdmErcfz4K_B2167h_tFzvHPJb4afRvDBvAXm0y0G-t1Dwn_0L0F3yd8lh_xOWjX34wP9xe-tTvbDtqlt-hgnQOcPMdj9Ovs63J-Xiwuv13MTxeF4azpi6qqNJUrLldVlTU0Uou15k3ZUFHW-TBSS8lEFsO1JKLWugJDaiYNcM7Nih-jD_u-2xjuBki92uSfgnPaQxiSYoQ3rJY1FRnK91ATQ0oR1mqbFek4KkrUZLTq1JPRajJ6KmajM-v984BhtYH2hfPX1gz4tAdAlrmzEFUy2RwDrY1getUG-58Bn__hG2e9NdrdwgipC0PMS0qKqsQUUVfTrqdVU8lJSaTkj04mpRU</recordid><startdate>20170401</startdate><enddate>20170401</enddate><creator>Porta-Sánchez, Andreu, MD</creator><creator>Spillane, David R., MSc, MDCM(c)</creator><creator>Harris, Louise, MD</creator><creator>Xue, Joel, PhD</creator><creator>Dorsey, Pat, BS</creator><creator>Care, Melanie, MSc</creator><creator>Chauhan, Vijay, MD</creator><creator>Gollob, Michael H., MD</creator><creator>Spears, Danna A., MD</creator><general>Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20170401</creationdate><title>T-Wave Morphology Analysis in Congenital Long QT Syndrome Discriminates Patients From Healthy Individuals</title><author>Porta-Sánchez, Andreu, MD ; Spillane, David R., MSc, MDCM(c) ; Harris, Louise, MD ; Xue, Joel, PhD ; Dorsey, Pat, BS ; Care, Melanie, MSc ; Chauhan, Vijay, MD ; Gollob, Michael H., MD ; Spears, Danna A., MD</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c329t-777a16b36b7740596a5fa3949154888820866255283a6058aa7ec0826ce333cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Cardiovascular</topic><topic>long QT syndrome</topic><topic>morphology combination score</topic><topic>principal component analysis</topic><topic>T-wave</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Porta-Sánchez, Andreu, MD</creatorcontrib><creatorcontrib>Spillane, David R., MSc, MDCM(c)</creatorcontrib><creatorcontrib>Harris, Louise, MD</creatorcontrib><creatorcontrib>Xue, Joel, PhD</creatorcontrib><creatorcontrib>Dorsey, Pat, BS</creatorcontrib><creatorcontrib>Care, Melanie, MSc</creatorcontrib><creatorcontrib>Chauhan, Vijay, MD</creatorcontrib><creatorcontrib>Gollob, Michael H., MD</creatorcontrib><creatorcontrib>Spears, Danna A., MD</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>JACC. Clinical electrophysiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Porta-Sánchez, Andreu, MD</au><au>Spillane, David R., MSc, MDCM(c)</au><au>Harris, Louise, MD</au><au>Xue, Joel, PhD</au><au>Dorsey, Pat, BS</au><au>Care, Melanie, MSc</au><au>Chauhan, Vijay, MD</au><au>Gollob, Michael H., MD</au><au>Spears, Danna A., MD</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>T-Wave Morphology Analysis in Congenital Long QT Syndrome Discriminates Patients From Healthy Individuals</atitle><jtitle>JACC. Clinical electrophysiology</jtitle><addtitle>JACC Clin Electrophysiol</addtitle><date>2017-04-01</date><risdate>2017</risdate><volume>3</volume><issue>4</issue><spage>374</spage><epage>381</epage><pages>374-381</pages><issn>2405-500X</issn><eissn>2405-5018</eissn><abstract><![CDATA[Abstract Objectives This study aims to assess the capability of T-wave analysis to: 1) identify genotype-positive long QT syndrome (LQTS) patients; 2) identify LQTS patients with borderline or normal QTc interval (≤460 ms); and 3) classify LQTS subtype. Background LQTS often presents with a nondiagnostic electrocardiogram (ECG). T-wave abnormalities may be the only marker of this potentially lethal arrhythmia syndrome. Methods ECGs taken at rest in 108 patients (43 with LQTS1, 20 with LQTS2, and 45 control subjects) were evaluated for T-wave flatness, asymmetry, and notching, which produces a morphology combination score (MCS) of the 3 features (MCS = 1.6 × flatness + asymmetry + notch) using QT Guard Plus Software (GE Healthcare, Milwaukee, Wisconsin). To assess for heterogeneity of repolarization, the principal component analysis ratio 2 (PCA-2) was calculated. Results Mean QTc intervals were 486 ± 50 ms (LQTS1), 479 ± 36 ms (LQTS2), and 418 ± 24 ms (control subjects) (p < 0.05). MCS and PCA-2 differed between LQTS patients and control subjects (MCS: 117.8 ± 57.4 vs. 71.9 ± 16.2; p < 0.001; PCA-2: 20.2 ± 10.4% vs. 14.6 ± 5.5%; p < 0.001), LQTS1 and LQTS2 patients (MCS: 96.3 ± 28.7 vs. 164 ± 75.2; p < 0.001; PCA-2: 17.8 ± 8.3% vs. 25 ± 12.6%; p < 0.001), and between LQTS patients with borderline or normal QTc intervals (n = 17) and control subjects (MCS: 105.7 ± 49.9 vs. 71.9 ± 16.2; p < 0.001; PCA-2: 18.1 ± 7.2% vs. 14.6 ± 5.5%; p < 0.001). T-wave metrics were consistent across multiple ECGs from individual patients based on the average intraclass correlation coefficient (MCS: 0.96; PCA-2: 0.86). Conclusions Automated T-wave morphology analysis accurately discriminates patients with pathogenic LQTS mutations from control subjects and between the 2 most common LQTS subtypes. Mutation carriers without baseline QTc prolongation were also identified. This may be a useful tool for screening families of LQTS patients, particularly when the QTc interval is subthreshold and genetic testing is unavailable.]]></abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>29759450</pmid><doi>10.1016/j.jacep.2016.10.013</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Cardiovascular long QT syndrome morphology combination score principal component analysis T-wave |
| title | T-Wave Morphology Analysis in Congenital Long QT Syndrome Discriminates Patients From Healthy Individuals |
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