QRS Vector Magnitude as Predictor of Ventricular Arrhythmia in Patients With Brugada Syndrome
Risk stratification is the most challenging part in management of patients with Brugada syndrome (BrS). Conduction delay in the right ventricular outflow tract (RVOT) is the major mechanism underlying ventricular tachyarrhythmia (VTA) in BrS. However, QRS duration was not useful in stratifying high-...
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container_title | The American journal of cardiology |
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creator | Ragab, Ahmed A.Y. Houck, Charlotte A. van der Does, Lisette J.M.E. Lanters, Eva A.H. Muskens, Agnes J.Q.M. de Groot, Natasja M.S. |
description | Risk stratification is the most challenging part in management of patients with Brugada syndrome (BrS). Conduction delay in the right ventricular outflow tract (RVOT) is the major mechanism underlying ventricular tachyarrhythmia (VTA) in BrS. However, QRS duration was not useful in stratifying high-risk patients in large registries. Reconstructing the traditional 12-lead electrocardiogram into QRS vector magnitude can be used to quantify depolarization dispersion and identify high-risk BrS patients. The aim of the study is to test the significance of the QRSvm as a predictor for VTA in patients with BrS. In this retrospective cohort, we included 136 patients (47 ± 15 years, 66% male) who visited outpatient clinic for cardiogenetic screening. All medical records were examined, all 12- lead electrocardiograms were reconstructed into QRSvm using Kors' quasiorthogonal method and were assessed for the presence of electrocardiographic signs indicative of RVOT conduction delay including R wave sign, deep SI, SII >SIII pattern, and Tzou criteria. QRSvm was significantly lower in patients who either presented with VTA or developed VTA during follow-up (1.24 ± 0.35 vs 1.78 ± 0.42 mV, p < 0.001). Positive RVOT conduction delay signs occurred more frequently in symptomatic patients (20% vs 7%, p < 0.001).The area under receiver operator characteristic curve for QRSvm was 0.85 (95% confidence interval [CI] 0.77 to 0.92). Using QRSvm cutoff of 1.55 mV, sensitivity and specificity were 89% and 71%, respectively. Multivariate regression analysis showed that QRSvm and RVOT signs are independent predictors for VTA in BrS patients (QRS vector magnitude: odds ratio 3.68, 95% CI 2.4 to 6.2, p = 0.001; RVOT: odds ratio 2.6, 95% CI 1.4 to 4.9, p = 0.001). In conclusion, not only electrocardiographic signs indicative of RVOT conduction delay but also QRSvm can be used as a predictor for VTA events in BrS patients. |
doi_str_mv | 10.1016/j.amjcard.2019.03.018 |
format | Article |
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Conduction delay in the right ventricular outflow tract (RVOT) is the major mechanism underlying ventricular tachyarrhythmia (VTA) in BrS. However, QRS duration was not useful in stratifying high-risk patients in large registries. Reconstructing the traditional 12-lead electrocardiogram into QRS vector magnitude can be used to quantify depolarization dispersion and identify high-risk BrS patients. The aim of the study is to test the significance of the QRSvm as a predictor for VTA in patients with BrS. In this retrospective cohort, we included 136 patients (47 ± 15 years, 66% male) who visited outpatient clinic for cardiogenetic screening. All medical records were examined, all 12- lead electrocardiograms were reconstructed into QRSvm using Kors' quasiorthogonal method and were assessed for the presence of electrocardiographic signs indicative of RVOT conduction delay including R wave sign, deep SI, SII >SIII pattern, and Tzou criteria. QRSvm was significantly lower in patients who either presented with VTA or developed VTA during follow-up (1.24 ± 0.35 vs 1.78 ± 0.42 mV, p < 0.001). Positive RVOT conduction delay signs occurred more frequently in symptomatic patients (20% vs 7%, p < 0.001).The area under receiver operator characteristic curve for QRSvm was 0.85 (95% confidence interval [CI] 0.77 to 0.92). Using QRSvm cutoff of 1.55 mV, sensitivity and specificity were 89% and 71%, respectively. Multivariate regression analysis showed that QRSvm and RVOT signs are independent predictors for VTA in BrS patients (QRS vector magnitude: odds ratio 3.68, 95% CI 2.4 to 6.2, p = 0.001; RVOT: odds ratio 2.6, 95% CI 1.4 to 4.9, p = 0.001). In conclusion, not only electrocardiographic signs indicative of RVOT conduction delay but also QRSvm can be used as a predictor for VTA events in BrS patients.</description><identifier>ISSN: 0002-9149</identifier><identifier>EISSN: 1879-1913</identifier><identifier>DOI: 10.1016/j.amjcard.2019.03.018</identifier><identifier>PMID: 30955864</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Age ; Arrhythmia ; Brugada Syndrome - complications ; Brugada Syndrome - physiopathology ; Cardiac arrhythmia ; Chronic obstructive pulmonary disease ; Conduction ; Confidence intervals ; Delay ; Depolarization ; EKG ; Electrocardiography ; Female ; Heart ; Heart Conduction System - physiopathology ; Humans ; Male ; Medical records ; Middle Aged ; Morphology ; Outpatient care facilities ; Patients ; Population ; Regression analysis ; Retrospective Studies ; Risk ; Risk groups ; Sensitivity analysis ; Sensitivity and Specificity ; Statistical analysis ; Tachyarrhythmia ; Tachycardia, Ventricular - diagnosis ; Tachycardia, Ventricular - etiology ; Tachycardia, Ventricular - physiopathology ; Ventricle</subject><ispartof>The American journal of cardiology, 2019-06, Vol.123 (12), p.1962-1966</ispartof><rights>2019 Elsevier Inc.</rights><rights>Copyright © 2019 Elsevier Inc. All rights reserved.</rights><rights>2019. Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c440t-7902acf406552b62277233145b32726820a0b04f7391ed30e6ed96a834f98c1a3</citedby><cites>FETCH-LOGICAL-c440t-7902acf406552b62277233145b32726820a0b04f7391ed30e6ed96a834f98c1a3</cites><orcidid>0000-0002-0259-6691</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0002914919303157$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30955864$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ragab, Ahmed A.Y.</creatorcontrib><creatorcontrib>Houck, Charlotte A.</creatorcontrib><creatorcontrib>van der Does, Lisette J.M.E.</creatorcontrib><creatorcontrib>Lanters, Eva A.H.</creatorcontrib><creatorcontrib>Muskens, Agnes J.Q.M.</creatorcontrib><creatorcontrib>de Groot, Natasja M.S.</creatorcontrib><title>QRS Vector Magnitude as Predictor of Ventricular Arrhythmia in Patients With Brugada Syndrome</title><title>The American journal of cardiology</title><addtitle>Am J Cardiol</addtitle><description>Risk stratification is the most challenging part in management of patients with Brugada syndrome (BrS). Conduction delay in the right ventricular outflow tract (RVOT) is the major mechanism underlying ventricular tachyarrhythmia (VTA) in BrS. However, QRS duration was not useful in stratifying high-risk patients in large registries. Reconstructing the traditional 12-lead electrocardiogram into QRS vector magnitude can be used to quantify depolarization dispersion and identify high-risk BrS patients. The aim of the study is to test the significance of the QRSvm as a predictor for VTA in patients with BrS. In this retrospective cohort, we included 136 patients (47 ± 15 years, 66% male) who visited outpatient clinic for cardiogenetic screening. All medical records were examined, all 12- lead electrocardiograms were reconstructed into QRSvm using Kors' quasiorthogonal method and were assessed for the presence of electrocardiographic signs indicative of RVOT conduction delay including R wave sign, deep SI, SII >SIII pattern, and Tzou criteria. QRSvm was significantly lower in patients who either presented with VTA or developed VTA during follow-up (1.24 ± 0.35 vs 1.78 ± 0.42 mV, p < 0.001). Positive RVOT conduction delay signs occurred more frequently in symptomatic patients (20% vs 7%, p < 0.001).The area under receiver operator characteristic curve for QRSvm was 0.85 (95% confidence interval [CI] 0.77 to 0.92). Using QRSvm cutoff of 1.55 mV, sensitivity and specificity were 89% and 71%, respectively. Multivariate regression analysis showed that QRSvm and RVOT signs are independent predictors for VTA in BrS patients (QRS vector magnitude: odds ratio 3.68, 95% CI 2.4 to 6.2, p = 0.001; RVOT: odds ratio 2.6, 95% CI 1.4 to 4.9, p = 0.001). In conclusion, not only electrocardiographic signs indicative of RVOT conduction delay but also QRSvm can be used as a predictor for VTA events in BrS patients.</description><subject>Adult</subject><subject>Age</subject><subject>Arrhythmia</subject><subject>Brugada Syndrome - complications</subject><subject>Brugada Syndrome - physiopathology</subject><subject>Cardiac arrhythmia</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Conduction</subject><subject>Confidence intervals</subject><subject>Delay</subject><subject>Depolarization</subject><subject>EKG</subject><subject>Electrocardiography</subject><subject>Female</subject><subject>Heart</subject><subject>Heart Conduction System - physiopathology</subject><subject>Humans</subject><subject>Male</subject><subject>Medical records</subject><subject>Middle Aged</subject><subject>Morphology</subject><subject>Outpatient care facilities</subject><subject>Patients</subject><subject>Population</subject><subject>Regression analysis</subject><subject>Retrospective Studies</subject><subject>Risk</subject><subject>Risk groups</subject><subject>Sensitivity analysis</subject><subject>Sensitivity and Specificity</subject><subject>Statistical analysis</subject><subject>Tachyarrhythmia</subject><subject>Tachycardia, Ventricular - 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complications</topic><topic>Brugada Syndrome - physiopathology</topic><topic>Cardiac arrhythmia</topic><topic>Chronic obstructive pulmonary disease</topic><topic>Conduction</topic><topic>Confidence intervals</topic><topic>Delay</topic><topic>Depolarization</topic><topic>EKG</topic><topic>Electrocardiography</topic><topic>Female</topic><topic>Heart</topic><topic>Heart Conduction System - physiopathology</topic><topic>Humans</topic><topic>Male</topic><topic>Medical records</topic><topic>Middle Aged</topic><topic>Morphology</topic><topic>Outpatient care facilities</topic><topic>Patients</topic><topic>Population</topic><topic>Regression analysis</topic><topic>Retrospective Studies</topic><topic>Risk</topic><topic>Risk groups</topic><topic>Sensitivity analysis</topic><topic>Sensitivity and Specificity</topic><topic>Statistical analysis</topic><topic>Tachyarrhythmia</topic><topic>Tachycardia, Ventricular - diagnosis</topic><topic>Tachycardia, Ventricular - etiology</topic><topic>Tachycardia, Ventricular - physiopathology</topic><topic>Ventricle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ragab, Ahmed A.Y.</creatorcontrib><creatorcontrib>Houck, Charlotte A.</creatorcontrib><creatorcontrib>van der Does, Lisette J.M.E.</creatorcontrib><creatorcontrib>Lanters, Eva A.H.</creatorcontrib><creatorcontrib>Muskens, Agnes J.Q.M.</creatorcontrib><creatorcontrib>de Groot, Natasja M.S.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biochemistry Abstracts 1</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>The American journal of cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ragab, Ahmed A.Y.</au><au>Houck, Charlotte A.</au><au>van der Does, Lisette J.M.E.</au><au>Lanters, Eva A.H.</au><au>Muskens, Agnes J.Q.M.</au><au>de Groot, Natasja M.S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>QRS Vector Magnitude as Predictor of Ventricular Arrhythmia in Patients With Brugada Syndrome</atitle><jtitle>The American journal of cardiology</jtitle><addtitle>Am J Cardiol</addtitle><date>2019-06-15</date><risdate>2019</risdate><volume>123</volume><issue>12</issue><spage>1962</spage><epage>1966</epage><pages>1962-1966</pages><issn>0002-9149</issn><eissn>1879-1913</eissn><abstract>Risk stratification is the most challenging part in management of patients with Brugada syndrome (BrS). Conduction delay in the right ventricular outflow tract (RVOT) is the major mechanism underlying ventricular tachyarrhythmia (VTA) in BrS. However, QRS duration was not useful in stratifying high-risk patients in large registries. Reconstructing the traditional 12-lead electrocardiogram into QRS vector magnitude can be used to quantify depolarization dispersion and identify high-risk BrS patients. The aim of the study is to test the significance of the QRSvm as a predictor for VTA in patients with BrS. In this retrospective cohort, we included 136 patients (47 ± 15 years, 66% male) who visited outpatient clinic for cardiogenetic screening. All medical records were examined, all 12- lead electrocardiograms were reconstructed into QRSvm using Kors' quasiorthogonal method and were assessed for the presence of electrocardiographic signs indicative of RVOT conduction delay including R wave sign, deep SI, SII >SIII pattern, and Tzou criteria. QRSvm was significantly lower in patients who either presented with VTA or developed VTA during follow-up (1.24 ± 0.35 vs 1.78 ± 0.42 mV, p < 0.001). Positive RVOT conduction delay signs occurred more frequently in symptomatic patients (20% vs 7%, p < 0.001).The area under receiver operator characteristic curve for QRSvm was 0.85 (95% confidence interval [CI] 0.77 to 0.92). Using QRSvm cutoff of 1.55 mV, sensitivity and specificity were 89% and 71%, respectively. Multivariate regression analysis showed that QRSvm and RVOT signs are independent predictors for VTA in BrS patients (QRS vector magnitude: odds ratio 3.68, 95% CI 2.4 to 6.2, p = 0.001; RVOT: odds ratio 2.6, 95% CI 1.4 to 4.9, p = 0.001). In conclusion, not only electrocardiographic signs indicative of RVOT conduction delay but also QRSvm can be used as a predictor for VTA events in BrS patients.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>30955864</pmid><doi>10.1016/j.amjcard.2019.03.018</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0002-0259-6691</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Age Arrhythmia Brugada Syndrome - complications Brugada Syndrome - physiopathology Cardiac arrhythmia Chronic obstructive pulmonary disease Conduction Confidence intervals Delay Depolarization EKG Electrocardiography Female Heart Heart Conduction System - physiopathology Humans Male Medical records Middle Aged Morphology Outpatient care facilities Patients Population Regression analysis Retrospective Studies Risk Risk groups Sensitivity analysis Sensitivity and Specificity Statistical analysis Tachyarrhythmia Tachycardia, Ventricular - diagnosis Tachycardia, Ventricular - etiology Tachycardia, Ventricular - physiopathology Ventricle |
title | QRS Vector Magnitude as Predictor of Ventricular Arrhythmia in Patients With Brugada Syndrome |
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