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Sigfstead S, Jiang R, Avram R, Davies B, Krahn AD, Cheung CC. Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes. Can J Cardiol 2024:S0828-282X(24)00335-0. [PMID: 38670456 DOI: 10.1016/j.cjca.2024.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/08/2024] [Accepted: 04/21/2024] [Indexed: 04/28/2024] Open
Abstract
Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in our understanding of these syndromes have improved patient diagnosis and care, yet certain clinical gaps remain, particularly within case ascertainment, access to genetic testing, and risk stratification. Artificial intelligence (AI), specifically machine learning and its subset deep learning, present promising solutions to these challenges. The capacity of AI to process vast amounts of patient data and identify disease patterns differentiates them from traditional methods, which are time- and resource-intensive. To date, AI models have shown immense potential in condition detection (including asymptomatic/concealed disease) and genotype and phenotype identification, exceeding expert cardiologists in these tasks. Additionally, they have exhibited applicability for general population screening, improving case ascertainment in a set of conditions that are often asymptomatic such as left ventricular dysfunction. Third, models have shown the ability to improve testing protocols; through model identification of disease and genotype, specific clinical testing (eg, drug challenges or further diagnostic imaging) can be avoided, reducing health care expenses, speeding diagnosis, and possibly allowing for more incremental or targeted genetic testing approaches. These significant benefits warrant continued investigation of AI, particularly regarding the development and implementation of clinically applicable screening tools. In this review we summarize key developments in AI, including studies in long QT syndrome, Brugada syndrome, hypertrophic cardiomyopathy, and arrhythmogenic cardiomyopathies, and provide direction for effective future AI implementation in clinical practice.
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Affiliation(s)
- Sophie Sigfstead
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - River Jiang
- Division of Cardiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert Avram
- Heartwise (heartwise.ai), Montreal Heart Institute, Montreal, Quebec, Canada; Department of Medicine, Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
| | - Brianna Davies
- Center for Cardiovascular Innovation, Division of Cardiology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Andrew D Krahn
- Center for Cardiovascular Innovation, Division of Cardiology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
| | - Christopher C Cheung
- Division of Cardiology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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Asatryan B, Bleijendaal H, Wilde AAM. Toward advanced diagnosis and management of inherited arrhythmia syndromes: Harnessing the capabilities of artificial intelligence and machine learning. Heart Rhythm 2023; 20:1399-1407. [PMID: 37442407 DOI: 10.1016/j.hrthm.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/20/2023] [Accepted: 07/02/2023] [Indexed: 07/15/2023]
Abstract
The use of advanced computational technologies, such as artificial intelligence (AI), is now exerting a significant influence on various aspects of life, including health care and science. AI has garnered remarkable public notice with the release of deep learning models that can model anything from artwork to academic papers with minimal human intervention. Machine learning, a method that uses algorithms to extract information from raw data and represent it in a model, and deep learning, a method that uses multiple layers to progressively extract higher-level features from the raw input with minimal human intervention, are increasingly leveraged to tackle problems in the health sector, including utilization for clinical decision support in cardiovascular medicine. Inherited arrhythmia syndromes are a clinical domain where multiple unanswered questions remain despite unprecedented progress over the past 2 decades with the introduction of large panel genetic testing and the first steps in precision medicine. In particular, AI tools can help address gaps in clinical diagnosis by identifying individuals with concealed or transient phenotypes; enhance risk stratification by elevating recognition of underlying risk burden beyond widely recognized risk factors; improve prediction of response to therapy, and further prognostication. In this contemporary review, we provide a summary of the AI models developed to solve challenges in inherited arrhythmia syndromes and also outline gaps that can be filled with the development of intelligent AI models.
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Affiliation(s)
- Babken Asatryan
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
| | - Hidde Bleijendaal
- University of Amsterdam, Heart Center; Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, The Netherlands; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, University of Amsterdam, Amsterdam, The Netherlands
| | - Arthur A M Wilde
- University of Amsterdam, Heart Center; Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, The Netherlands; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, University of Amsterdam, Amsterdam, The Netherlands; European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-Heart)
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Akbuğa K, Karanfil M. Same family, same mutation, different ECG. Mol Genet Genomic Med 2022; 11:e2079. [PMID: 36305573 PMCID: PMC9834179 DOI: 10.1002/mgg3.2079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/01/2022] [Accepted: 10/21/2022] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Different types of long QT syndromes (LQTS) have distinct ECG manifestations according to the type and magnitude of ion channel dysfunction. While LQT1 carriers usually have broad-based T waves and LQT3 carriers have extended ST segments with relatively narrow peaked T waves; LQT2 carriers have low-amplitude T waves with high incidences of notches. METHODS We describe three members of a family with the same LQTS2 pathogenic variant, but different surface ECG findings. CONCLUSION This case shows ECG differences may also occur between family members who have pathogenic variants associated with long QT syndrome.
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Affiliation(s)
- Kürşat Akbuğa
- Cardiology Department, Faculty of MedicineTOBB ETUAnkaraTurkey
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Bleijendaal H, Croon PM, Pool MDO, Malekzadeh A, Aufiero S, Amin AS, Zwinderman AH, Pinto YM, Wilde AA, Winter MM. Clinical applicability of artificial intelligence for patients with an inherited heart disease: a scoping review. Trends Cardiovasc Med 2022:S1050-1738(22)00013-5. [DOI: 10.1016/j.tcm.2022.01.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 01/06/2022] [Accepted: 01/23/2022] [Indexed: 01/22/2023]
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Shakibfar S, Graff C, Kanters JK, Nielsen J, Schmidt S, Struijk JJ. Minimal T-wave representation and its use in the assessment of drug arrhythmogenicity. Ann Noninvasive Electrocardiol 2017; 22. [DOI: 10.1111/anec.12413] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Affiliation(s)
- Saeed Shakibfar
- Center for Sensory Motor Interaction (SMI); Department of Health Science and Technology; Aalborg University; Aalborg Denmark
| | - Claus Graff
- Medical Informatics Group (MI); Department of Health Science and Technology; Aalborg University; Aalborg Denmark
| | - Jørgen K. Kanters
- Laboratory of Experimental Cardiology; Department of Biomedical Sciences; University of Copenhagen; Copenhagen Denmark
- Department of Cardiology; Herlev & Gentofte University Hospitals; Copenhagen Denmark
- Department of Cardiology; Aalborg University Hospital; Aalborg Denmark
| | - Jimmi Nielsen
- Center for Schizophrenia; Aalborg Psychiatric Hospital; Aalborg University Hospital; Aalborg Denmark
| | - Samuel Schmidt
- Medical Informatics Group (MI); Department of Health Science and Technology; Aalborg University; Aalborg Denmark
| | - Johannes J. Struijk
- Medical Informatics Group (MI); Department of Health Science and Technology; Aalborg University; Aalborg Denmark
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Hyltén-Cavallius L, Iepsen EW, Christiansen M, Graff C, Linneberg A, Pedersen O, Holst JJ, Hansen T, Torekov SS, Kanters JK. Glucose ingestion causes cardiac repolarization disturbances in type 1 long QT syndrome patients and healthy subjects. Heart Rhythm 2017; 14:1165-1170. [PMID: 28400316 DOI: 10.1016/j.hrthm.2017.04.018] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Indexed: 10/19/2022]
Abstract
BACKGROUND Both hypoglycemia and severe hyperglycemia constitute known risk factors for cardiac repolarization changes potentially leading to malignant arrhythmias. Patients with loss of function mutations in KCNQ1 are characterized by long QT syndrome (LQTS) and may be at increased risk for glucose-induced repolarization disturbances. OBJECTIVE The purpose of this study was to test the hypothesis that KCNQ1 LQTS patients are at particular risk for cardiac repolarization changes during the relative hyperglycemia that occurs after an oral glucose load. METHODS Fourteen KCNQ1 LQTS patients and 28 control participants matched for gender, body mass index, and age underwent a 3-hour oral 75-g glucose tolerance test with ECGs obtained at 7 time points. Fridericia corrected QT interval (QTcF), Bazett corrected QT interval (QTcB), and the Morphology Combination Score (MCS) were calculated. RESULTS QTc and MCS increased in both groups. MCS remained elevated until 150 minutes after glucose ingestion, and the maximal change from baseline was larger among KCNQ1 LQTS patients compared with control subjects (0.28 ± 0.27 vs 0.15 ± 0.13; P <.05). CONCLUSION Relative hyperglycemia induced by ingestion of 75-g glucose caused cardiac repolarization disturbances that were more severe in KCNQ1 LQTS patients compared with control subjects.
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Affiliation(s)
- Louise Hyltén-Cavallius
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Eva W Iepsen
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael Christiansen
- Department of Clinical Biochemistry, Statens Serum Institut, Copenhagen, Denmark
| | - Claus Graff
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Allan Linneberg
- Research Centre for Prevention and Health, The Capital Region, Copenhagen, Denmark; Department of Clinical Experimental Research, Rigshospitalet, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens J Holst
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Signe S Torekov
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jørgen K Kanters
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Cardiology S, Gentofte University Hospital, Copenhagen, Denmark.
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Porta-Sánchez A, Spillane DR, Harris L, Xue J, Dorsey P, Care M, Chauhan V, Gollob MH, Spears DA. T-Wave Morphology Analysis in Congenital Long QT Syndrome Discriminates Patients From Healthy Individuals. JACC Clin Electrophysiol 2016; 3:374-381. [PMID: 29759450 DOI: 10.1016/j.jacep.2016.10.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 10/18/2016] [Accepted: 10/20/2016] [Indexed: 10/20/2022]
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.
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Affiliation(s)
- Andreu Porta-Sánchez
- Division of Cardiology, Peter Munk Cardiac Center, University Health Network, Toronto, Ontario, Canada
| | - David R Spillane
- Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Louise Harris
- Division of Cardiology, Peter Munk Cardiac Center, University Health Network, Toronto, Ontario, Canada
| | - Joel Xue
- GE Healthcare, Wauwatosa, Wisconsin
| | | | | | - Vijay Chauhan
- Division of Cardiology, Peter Munk Cardiac Center, University Health Network, Toronto, Ontario, Canada
| | - Michael H Gollob
- Division of Cardiology, Peter Munk Cardiac Center, University Health Network, Toronto, Ontario, Canada
| | - Danna A Spears
- Division of Cardiology, Peter Munk Cardiac Center, University Health Network, Toronto, Ontario, Canada.
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Immanuel SA, Sadrieh A, Baumert M, Couderc JP, Zareba W, Hill AP, Vandenberg JI. T-wave morphology can distinguish healthy controls from LQTS patients. Physiol Meas 2016; 37:1456-73. [PMID: 27510854 DOI: 10.1088/0967-3334/37/9/1456] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Long QT syndrome (LQTS) is an inherited disorder associated with prolongation of the QT/QTc interval on the surface electrocardiogram (ECG) and a markedly increased risk of sudden cardiac death due to cardiac arrhythmias. Up to 25% of genotype-positive LQTS patients have QT/QTc intervals in the normal range. These patients are, however, still at increased risk of life-threatening events compared to their genotype-negative siblings. Previous studies have shown that analysis of T-wave morphology may enhance discrimination between control and LQTS patients. In this study we tested the hypothesis that automated analysis of T-wave morphology from Holter ECG recordings could distinguish between control and LQTS patients with QTc values in the range 400-450 ms. Holter ECGs were obtained from the Telemetric and Holter ECG Warehouse (THEW) database. Frequency binned averaged ECG waveforms were obtained and extracted T-waves were fitted with a combination of 3 sigmoid functions (upslope, downslope and switch) or two 9th order polynomial functions (upslope and downslope). Neural network classifiers, based on parameters obtained from the sigmoid or polynomial fits to the 1 Hz and 1.3 Hz ECG waveforms, were able to achieve up to 92% discrimination between control and LQTS patients and 88% discrimination between LQTS1 and LQTS2 patients. When we analysed a subgroup of subjects with normal QT intervals (400-450 ms, 67 controls and 61 LQTS), T-wave morphology based parameters enabled 90% discrimination between control and LQTS patients, compared to only 71% when the groups were classified based on QTc alone. In summary, our Holter ECG analysis algorithms demonstrate the feasibility of using automated analysis of T-wave morphology to distinguish LQTS patients, even those with normal QTc, from healthy controls.
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Affiliation(s)
- S A Immanuel
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Sydney, Australia. Department of Electrical and Electronics Engineering, University of Adelaide, Adelaide, Australia
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The T-peak–T-end Interval as a Marker of Repolarization Abnormality: A Comparison with the QT Interval for Five Different Drugs. Clin Drug Investig 2015; 35:717-24. [DOI: 10.1007/s40261-015-0328-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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10
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Meijborg VM, Chauveau S, Janse MJ, Anyukhovsky EP, Danilo PR, Rosen MR, Opthof T, Coronel R. Interventricular dispersion in repolarization causes bifid T waves in dogs with dofetilide-induced long QT syndrome. Heart Rhythm 2015; 12:1343-51. [DOI: 10.1016/j.hrthm.2015.02.026] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2014] [Indexed: 11/27/2022]
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Hong L, Andersen L, Graff C, Vedel-Larsen E, Wang F, Struijk J, Sogaard P, Hansen P, Yang Y, Christiansen M, Toft E, Kanters J. T-wave morphology analysis of competitive athletes. J Electrocardiol 2015; 48:35-42. [DOI: 10.1016/j.jelectrocard.2014.10.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Indexed: 12/09/2022]
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Hedley PL, Durrheim GA, Hendricks F, Goosen A, Jespersgaard C, Støvring B, Pham TT, Christiansen M, Brink PA, Corfield VA. Long QT syndrome in South Africa: the results of comprehensive genetic screening. Cardiovasc J Afr 2014; 24:231-7. [PMID: 24217263 PMCID: PMC3772322 DOI: 10.5830/cvja-2013-032] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2013] [Accepted: 05/24/2013] [Indexed: 01/06/2023] Open
Abstract
Congenital long QT syndrome (cLQTS) is a genetic disorder predisposing to ventricular arrhythmia, syncope and sudden death. Over 700 different cLQTS-causing mutations in 13 genes are known. The genetic spectrum of LQTS in 44 South African cLQTS patients (23 known to carry the South African founder mutation p.A341V in KCNQ1) was established by screening for mutations in the coding regions of KCNQ1, KCNH2, KCNE1, KCNE2 and SCN5A, the most frequently implicated cLQTS-causing genes (five-gene screening). Fourteen disease-causing mutations were identified, eight (including the founder mutation) in KCNQ1, five in KCNH2 and one in KCNE1. Two mutations were novel. Two double heterozygotes were found among the 23 families (8.5%) carrying the founder mutation. In conclusion, cLQTS in South Africa reflects both a strong founder effect and a genetic spectrum similar to that seen in other populations. Consequently, five-gene screening should be offered as a standard screening option, as is the case internationally. This will disclose compound and double heterozygotes. Fivegene screening will most likely be even more informative in other South African sub-populations with a greater genetic diversity.
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Affiliation(s)
- Paula L Hedley
- US/MRC Centre for Molecular and Cellular Biology, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, University of Stellenbosch, South Africa
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Sauer AJ, Kaplan R, Xue J, Dorsey P, Hayes M, Shah SJ, Passman R. Electrocardiographic markers of repolarization heterogeneity during dofetilide or sotalol initiation for paroxysmal atrial fibrillation. Am J Cardiol 2014; 113:2030-5. [PMID: 24793679 DOI: 10.1016/j.amjcard.2014.03.047] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2014] [Revised: 03/06/2014] [Accepted: 03/06/2014] [Indexed: 10/25/2022]
Abstract
Serial electrocardiographic monitoring of ΔQTc as an assumed harbinger of proarrhythmia is currently recommended for dofetilide and sotalol initiation. Markers of repolarization heterogeneity such as increased peak to end of T-wave (TpTe) duration and abnormal T-wave morphology may also predict proarrhythmia. We investigated whether such T-wave measurements on baseline electrocardiogram will correlate with ΔQTc after drug initiation. An analysis of 140 consecutive patients with paroxysmal atrial fibrillation hospitalized in sinus rhythm for sotalol or dofetilide initiation was performed. Baseline and serial electrocardiograms were analyzed using QT Guard Plus software (GE Healthcare), which measured QTc and TpTe and scored T-wave morphology for asymmetry, notching, and flatness using T-wave vector magnitude and principal component analysis algorithms. Sotalol and dofetilide were administered in 71% and 29% of patients, respectively. Mean age was 61 ± 14 years, and 34% were women. After a single dose of either drug, there was a statistically significant increase in QTc and TpTe (p <0.01), as well as composite and individual T-wave markers of repolarization heterogeneity (p <0.01). QTc increased by a mean of 19 ± 30 ms after initial antiarrhythmic dose. ΔQTc was inversely related to baseline QTc and TpTe (p <0.01). After controlling for baseline QTc, there was no independent association between T-wave markers of repolarization heterogeneity and ΔQTc. In conclusion, for patients with paroxysmal atrial fibrillation admitted for dofetilide or sotalol loading, T-wave markers of increased repolarization heterogeneity are measurable within hours after initiation. A shorter baseline QTc is associated with an increased ΔQTc; however, there is no independent relation between baseline T-wave markers of repolarization heterogeneity and ΔQTc.
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Christiansen M, Hedley PL, Theilade J, Stoevring B, Leren TP, Eschen O, Sørensen KM, Tybjærg-Hansen A, Ousager LB, Pedersen LN, Frikke-Schmidt R, Aidt FH, Hansen MG, Hansen J, Bloch Thomsen PE, Toft E, Henriksen FL, Bundgaard H, Jensen HK, Kanters JK. Mutations in Danish patients with long QT syndrome and the identification of a large founder family with p.F29L in KCNH2. BMC MEDICAL GENETICS 2014; 15:31. [PMID: 24606995 PMCID: PMC4007532 DOI: 10.1186/1471-2350-15-31] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2013] [Accepted: 02/18/2014] [Indexed: 01/08/2023]
Abstract
Background Long QT syndrome (LQTS) is a cardiac ion channelopathy which presents clinically with palpitations, syncope or sudden death. More than 700 LQTS-causing mutations have been identified in 13 genes, all of which encode proteins involved in the execution of the cardiac action potential. The most frequently affected genes, covering > 90% of cases, are KCNQ1, KCNH2 and SCN5A. Methods We describe 64 different mutations in 70 unrelated Danish families using a routine five-gene screen, comprising KCNQ1, KCNH2 and SCN5A as well as KCNE1 and KCNE2. Results Twenty-two mutations were found in KCNQ1, 28 in KCNH2, 9 in SCN5A, 3 in KCNE1 and 2 in KCNE2. Twenty-six of these have only been described in the Danish population and 18 are novel. One double heterozygote (1.4% of families) was found. A founder mutation, p.F29L in KCNH2, was identified in 5 “unrelated” families. Disease association, in 31.2% of cases, was based on the type of mutation identified (nonsense, insertion/deletion, frameshift or splice-site). Functional data was available for 22.7% of the missense mutations. None of the mutations were found in 364 Danish alleles and only three, all functionally characterised, were recorded in the Exome Variation Server, albeit at a frequency of < 1:1000. Conclusion The genetic etiology of LQTS in Denmark is similar to that found in other populations. A large founder family with p.F29L in KCNH2 was identified. In 48.4% of the mutations disease causation was based on mutation type or functional analysis.
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Affiliation(s)
- Michael Christiansen
- Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, Ørestads Boulevard 5, 2300S, Copenhagen, Denmark.
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The phenotype characteristics of type 13 long QT syndrome with mutation in KCNJ5 (Kir3.4-G387R). Heart Rhythm 2013; 10:1500-6. [PMID: 23872692 DOI: 10.1016/j.hrthm.2013.07.022] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Indexed: 11/24/2022]
Abstract
BACKGROUND Long QT syndrome type 13 (LQT13) is caused by loss-of-function mutation in the KCNJ5-encoded cardiac G-protein-coupled inward rectifier potassium channel subtype 4 protein. The electrocardiographic (ECG) features of LQT13 are not described yet. OBJECTIVE To describe for the first time in detail the phenotype-genotype relationship of the ECG and clinical features in patients with LQT13. METHODS The 12-lead ECGs, 24-hour Holter recordings, and clinical information from KCNJ5-G387R mutation carriers of a fourth-generation Han Chinese family with LQT13 and a group of healthy Chinese individuals were analyzed. RESULTS Compared with the analysis of the healthy group (n = 8), age- and sex-matched pair analysis revealed that the mutation carriers (n = 8) had ventricular repolarization abnormality results in the prolongation of corrected QT and QTpeak intervals (P < .01); greater combined measure of repolarization morphology (T-wave morphology combination score) based on asymmetry, flatness, and notch (P < .01); and reduced low frequency/high frequency ratio of heart rate variability (P < .01) as a reflection of cardiac autonomic imbalance. Mean heart rate, time domain parameters of heart rate variability, time interval from T-wave peak to T-wave end, and T-wave amplitude were similar. CONCLUSIONS This study demonstrates for the first time the ECG features of patients with LQT13. Our data suggest that QTpeak intervals and T-wave morphology combination score may be the better parameters than the corrected QT interval to predict the phenotype-genotype relationship in patients with LQT13.
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Gao Y, Li C, Liu W, Wu R, Qiu X, Liang R, Li L, Zhang L, Hu D. Genotype-phenotype analysis of three Chinese families with Jervell and Lange-Nielsen syndrome. J Cardiovasc Dis Res 2012; 3:67-75. [PMID: 22629021 PMCID: PMC3354473 DOI: 10.4103/0975-3583.95357] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Long QT syndrome (LQTS) is characterized by QT prolongation, syncope and sudden death. This study aims to explore the causes, clinical manifestations and therapeutic outcomes of Jervell and Lange-Nielsen syndrome (JLNS), a rare form of LQTS with congenital sensorineural deafness, in Chinese individuals. MATERIALS AND METHODS Three JLNS kindreds from the Chinese National LQTS Registry were investigated. Mutational screening of KCNQ1 and KCNE1 genes was performed by polymerase chain reaction and direct DNA sequence analysis. LQTS phenotype and therapeutic outcomes were evaluated for all probands and family members. RESULTS We identified 7 KCNQ1 mutations. c.1032_1117dup (p.Ser373TrpfsX10) and c.1319delT (p.Val440AlafsX26) were novel, causing JLNS in a 16-year-old boy with a QTc (QT interval corrected for heart rate) of 620 ms and recurrent syncope. c.605-2A>G and c.815G>A (p.Gly272Asp) caused JLNS in a 12-year-old girl and her 5-year-old brother, showing QTc of 590 to 600 ms and recurrent syncope. The fourth JLNS case, a 46-year-old man carrying c.1032G>A (p.Ala344Alasp) and c.569G>A (p.Arg190Gln) and with QTc of 460 ms, has been syncope-free since age 30. His 16-year-old daughter carries novel missense mutation c.574C>T (p.Arg192Cys) and c.1032G>A(p.Ala344Alasp) and displayed a severe phenotype of Romano-Ward syndrome (RWS) characterized by a QTc of 530 ms and recurrent syncope with normal hearing. Both the father and daughter also carried c.253G>A (p.Asp85Asn; rs1805128), a rare single nucleotide polymorphism (SNP) on KCNE1. Bizarre T waves were seen in 3/4 JLNS patients. Symptoms were improved and T wave abnormalities became less abnormal after appropriate treatment. CONCLUSION This study broadens the mutation and phenotype spectrums of JLNS. Compound heterozygous KCNQ1 mutations can result in both JLNS and severe forms of RWS in Chinese individuals.
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Affiliation(s)
- Yuanfeng Gao
- Heart Center, Peking University People's Hospital, Beijing - 100 044, P. R. China
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Graff C, Struijk JJ, Kanters JK, Andersen MP, Toft E, Tyl B. Effects of bilastine on T-wave morphology and the QTc interval: a randomized, double-blind, placebo-controlled, thorough QTc study. Clin Drug Investig 2012; 32:339-51. [PMID: 22393898 DOI: 10.2165/11599270-000000000-00000] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND AND OBJECTIVES The International Conference of Harmonisation (ICH) E14 guideline for thorough QT studies requires assessing the propensity of new non-antiarrhythmic drugs to affect cardiac repolarization. The present study investigates whether a composite ECG measure of T-wave morphology (Morphology Combination Score [MCS]) can be used together with the heart rate corrected QT interval (QTc) in a fully ICH E14-compliant thorough QT study to exclude clinically relevant repolarization effects of bilastine, a novel antihistamine. METHODS Thirty participants in this crossover study were randomly assigned to receive placebo, moxifloxacin 400 mg, bilastine at therapeutic and supratherapeutic doses (20 and 100 mg) and bilastine 20 mg co-administered with ketoconazole 400 mg. Resting ECGs recorded at 12 nominal time points before and after treatments were used to determine Fridericia corrected QTc (QTcF) and MCS from the T-wave characteristics: asymmetry, flatness and notching. RESULTS There were no effects of bilastine monotherapy (20 and 100 mg) on MCS or QTcF at those study times where the bilastine plasma concentrations were highest. MCS changes for bilastine monotherapy did not exceed the normal intrasubject variance of T-wave shapes for triplicate ECG recordings. Maximum QTcF prolongation for bilastine monotherapy was 5 ms or less: 3.8 ms (90% CI 0.3, 7.3 ms) for bilastine 20 mg and 5.0 ms (90% CI 2.0, 8.0 ms) for bilastine 100 mg. There were no indications of bilastine inducing larger repolarization effects on T-wave morphology as compared with the QTcF interval, as evidenced by the similarity of z-score equivalents for placebo-corrected changes in MCS and QTcF values. CONCLUSION This study shows that bilastine, at therapeutic and supratherapeutic dosages, does not induce any effects on T-wave morphology or QTcF. These results confirm the absence of an effect for bilastine on cardiac repolarization.
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Affiliation(s)
- Claus Graff
- Medical Informatics Group, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
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Winkel BG, Larsen MK, Berge KE, Leren TP, Nissen PH, Olesen MS, Hollegaard MV, Jespersen T, Yuan L, Nielsen N, Haunsø S, Svendsen JH, Wang Y, Kristensen IB, Jensen HK, Tfelt-Hansen J, Banner J. The prevalence of mutations in KCNQ1, KCNH2, and SCN5A in an unselected national cohort of young sudden unexplained death cases. J Cardiovasc Electrophysiol 2012; 23:1092-8. [PMID: 22882672 DOI: 10.1111/j.1540-8167.2012.02371.x] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
INTRODUCTION Sudden unexplained death account for one-third of all sudden natural deaths in the young (1-35 years). Hitherto, the prevalence of genopositive cases has primarily been based on deceased persons referred for postmortem genetic testing. These deaths potentially may represent the worst of cases, thus possibly overestimating the prevalence of potentially disease causing mutations in the 3 major long-QT syndrome (LQTS) genes in the general population. We therefore wanted to investigate the prevalence of mutations in an unselected population of sudden unexplained deaths in a nationwide setting. METHODS DNA for genetic testing was available for 44 cases of sudden unexplained death in Denmark in the period 2000-2006 (equaling 33% of all cases of sudden unexplained death in the age group). KCNQ1, KCNH2, and SCN5A were sequenced and in vitro electrophysiological studies were performed on novel mutations. RESULTS In total, 5 of 44 cases (11%) carried a mutation in 1 of the 3 genes corresponding to 11% of all investigated cases (R190W KCNQ1, F29L KCNH2 (2 cases), P297S KCNH2 and P1177L SCN5A). P1177L SCN5A has not been reported before. In vitro electrophysiological studies of P1177L SCN5A revealed an increased sustained current suggesting a LQTS phenotype. CONCLUSION In a nationwide setting, the genetic investigation of an unselected population of sudden unexplained death cases aged 1-35 years finds a lower than expected number of mutations compared to referred populations previously reported. We therefore conclude that the prevalence of mutations in the 3 major LQTS associated genes may not be as abundant as previously estimated.
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Affiliation(s)
- Bo Gregers Winkel
- Department of Cardiology, Rigshospitalet and Danish National Research Foundation Centre for Cardiac Arrhythmia (DARC), Copenhagen, Denmark.
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Shakibfar S, Graff C, Ehlers LH, Toft E, Kanters JK, Struijk JJ. Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval. Comput Biol Med 2012; 42:485-91. [DOI: 10.1016/j.compbiomed.2012.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2011] [Revised: 01/03/2012] [Accepted: 01/06/2012] [Indexed: 10/14/2022]
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Sy RW, van der Werf C, Chattha IS, Chockalingam P, Adler A, Healey JS, Perrin M, Gollob MH, Skanes AC, Yee R, Gula LJ, Leong-Sit P, Viskin S, Klein GJ, Wilde AA, Krahn AD. Derivation and Validation of a Simple Exercise-Based Algorithm for Prediction of Genetic Testing in Relatives of LQTS Probands. Circulation 2011; 124:2187-94. [DOI: 10.1161/circulationaha.111.028258] [Citation(s) in RCA: 155] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background—
Genetic testing can diagnose long-QT syndrome (LQTS) in asymptomatic relatives of patients with an identified mutation; however, it is costly and subject to availability. The accuracy of a simple algorithm that incorporates resting and exercise ECG parameters for screening LQTS in asymptomatic relatives was evaluated, with genetic testing as the gold standard.
Methods and Results—
Asymptomatic first-degree relatives of genetically characterized probands were recruited from 5 centers. QT intervals were measured at rest, during exercise, and during recovery. Receiver operating characteristics were used to establish optimal cutoffs. An algorithm for identifying LQTS carriers was developed in a derivation cohort and validated in an independent cohort. The derivation cohort consisted of 69 relatives (28 with LQT1, 20 with LQT2, and 21 noncarriers). Mean age was 35±18 years, and resting corrected QT interval (QTc) was 466±39 ms. Abnormal resting QTc (females ≥480 ms; males ≥470 ms) was 100% specific for gene carrier status, but was observed in only 48% of patients; however, mutations were observed in 68% and 42% of patients with a borderline or normal resting QTc, respectively. Among these patients, 4-minute recovery QTc ≥445 ms correctly restratified 22 of 25 patients as having LQTS and 19 of 21 patients as being noncarriers. The combination of resting and 4-minute recovery QTc in a screening algorithm yielded a sensitivity of 0.94 and specificity of 0.90 for detecting LQTS carriers. When applied to the validation cohort (n=152; 58 with LQT1, 61 with LQT2, and 33 noncarriers; QTc=443±47 ms), sensitivity was 0.92 and specificity was 0.82.
Conclusions—
A simple algorithm that incorporates resting and exercise-recovery QTc is useful in identifying LQTS in asymptomatic relatives.
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Affiliation(s)
- Raymond W. Sy
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Christian van der Werf
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Ishvinder S. Chattha
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Priya Chockalingam
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Arnon Adler
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Jeffrey S. Healey
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Mark Perrin
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Michael H. Gollob
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Allan C. Skanes
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Raymond Yee
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Lorne J. Gula
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Peter Leong-Sit
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Sami Viskin
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - George J. Klein
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Arthur A. Wilde
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
| | - Andrew D. Krahn
- From the University of Western Ontario, London, ON, Canada (R.W.S., I.S.C., A.C.S., R.Y., L.J.G., P.L.-S., G.J.K., A.D.K.); Academic Medical Center, Amsterdam, Netherlands (C.V.d.W., P.C., A.A.W.); Tel Aviv University, Tel Aviv, Israel (A.A., S.V.); McMaster University, Hamilton, ON, Canada (J.S.H.); and University of Ottawa, Ottawa, ON, Canada (M.P., M.H.G.)
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Nielsen J, Graff C, Kanters JK, Toft E, Taylor D, Meyer JM. Assessing QT interval prolongation and its associated risks with antipsychotics. CNS Drugs 2011; 25:473-90. [PMID: 21649448 DOI: 10.2165/11587800-000000000-00000] [Citation(s) in RCA: 89] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Several antipsychotics are associated with the ventricular tachycardia torsade de pointes (TdP), which may lead to sudden cardiac death (SCD), because of their inhibition of the cardiac delayed potassium rectifier channel. This inhibition extends the repolarization process of the ventricles of the heart, illustrated as a prolongation of the QT interval on a surface ECG. SCD in individuals receiving antipsychotics has an incidence of approximately 15 cases per 10,000 years of drug exposure but the exact association with TdP remains unknown because the diagnosis of TdP is uncertain. Most patients manifesting antipsychotic-associated TdP and subsequently SCD have well established risk factors for SCD, i.e. older age, female gender, hypokalaemia and cardiovascular disease. QT interval prolongation is the most widely used surrogate marker for assessing the risk of TdP but it is considered somewhat imprecise, partly because QT interval changes are subject to measurement error. In particular, drug-induced T-wave changes (e.g. flattening of the T-wave) may complicate the measurement of the QT interval. Furthermore, the QT interval depends on the heart rate and a corrected QT (QTc) interval is often used to compensate for this. Several correction formulas have been suggested, with Bazett's formula the most widely used. However, Bazett's formula overcorrects at a heart rate above 80 beats per minute and, therefore, Fridericia's formula is considered more appropriate to use in these cases. Several other surrogate markers for TdP have been developed but none of them is clinically implemented yet and QT interval prolongation is still considered the most valid surrogate marker. Although automated QT interval determination may offer some assistance, QT interval determination is best performed by a cardiologist skilled in its measurement. A QT interval >500 ms markedly increases the risk for TdP and SCD, and should lead to discontinuation of the offending drug and, if present, correction of underlying electrolyte disturbances, particularly serum potassium and magnesium derangements. Before prescribing antipsychotics that may increase the QTc interval, the clinician should ask about family and personal history of SCD, presyncope, syncope and cardiac arrhythmias, and recommend cardiology consultation if history is positive.
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Affiliation(s)
- Jimmi Nielsen
- Unit for Psychiatric Research, Aalborg Psychiatric Hospital, Aarhus University Hospital, Aalborg, Denmark.
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Prevalence of HCM and long QT syndrome mutations in young sudden cardiac death-related cases. Int J Legal Med 2011; 125:565-72. [PMID: 21499742 DOI: 10.1007/s00414-011-0572-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2010] [Accepted: 04/01/2011] [Indexed: 01/08/2023]
Abstract
Cardiomyopathies and channelopathies are major causes of sudden cardiac death. The genetic study of these diseases is difficult because of their heterogenic nature not only in their genetic traits but also in their phenotypic expression. The purpose of the present study is the analysis of a wide spectrum of previously known genetic mutations in key genes related to hypertrophic cardiomyopathy (HCM), long QT syndrome (LQTS), and Brugada syndrome (BrS) development. The samples studied include cases of sudden cardiac death (SCD) in young adults and their relatives in order to identify the real impact of genetic screening of SCD in forensic cases. Genetic screening of described variation in 16 genes implicated in the development of HCM and three more genes implicated in LQTS and BrS was performed by using MassARRAY technology. In addition, direct sequencing of the two most prevalent genes implicated in the development of SQTL type 1 and 2 was also carried out. Genetic screening allowed us to unmask four possibly pathogenic mutation carriers in the 49 SCD cases considered; carriers of mutation represent 9% (2/23) of the probands with structural anomalies found after autopsy and 7% (1/14) of the probands with structurally normal hearts after in depth autopsy protocol. One mutation was found among 12 of the recovered SCD cases considered. In people with direct family history of sudden cardiac death, but not themselves, 11 additional mutation carriers were found. Three different mutations were found in six of the 19 LQTS patients, representing three families and two different mutations were found among six patients with previous syncope. Genetic analysis in sudden cardiac death cases could help to elucidate the cause of death, but it also can help in the prevention of future deaths in families at risk. The study presented here shows the importance and relevance of genetic screening in patients with signs of cardiac hypertrophy and in family cases with more than one relative affected.
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Muñoz-Pichardo JM, Enguix-González A, Muñoz-García J, Moreno-Rebollo JL. Influence Analysis on Discriminant Coordinates. COMMUN STAT-SIMUL C 2011. [DOI: 10.1080/03610918.2011.556288] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Zhang T, Moss A, Cong P, Pan M, Chang B, Zheng L, Fang Q, Zareba W, Robinson J, Lin C, Li Z, Wei J, Zeng Q, Qi M. LQTS gene LOVD database. Hum Mutat 2010; 31:E1801-10. [PMID: 20809527 PMCID: PMC3037562 DOI: 10.1002/humu.21341] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The Long QT Syndrome (LQTS) is a group of genetically heterogeneous disorders that predisposes young individuals to ventricular arrhythmias and sudden death. LQTS is mainly caused by mutations in genes encoding subunits of cardiac ion channels (KCNQ1, KCNH2,SCN5A, KCNE1, and KCNE2). Many other genes involved in LQTS have been described recently(KCNJ2, AKAP9, ANK2, CACNA1C, SCNA4B, SNTA1, and CAV3). We created an online database(http://www.genomed.org/LOVD/introduction.html) that provides information on variants in LQTS-associated genes. As of February 2010, the database contains 1738 unique variants in 12 genes. A total of 950 variants are considered pathogenic, 265 are possible pathogenic, 131 are unknown/unclassified, and 292 have no known pathogenicity. In addition to these mutations collected from published literature, we also submitted information on gene variants, including one possible novel pathogenic mutation in the KCNH2 splice site found in ten Chinese families with documented arrhythmias. The remote user is able to search the data and is encouraged to submit new mutations into the database. The LQTS database will become a powerful tool for both researchers and clinicians.
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Affiliation(s)
- Tao Zhang
- James D. Watson Institute of Genome Sciences, College of Life Sciences, Zhejiang UniversityHangzhou, Zhejiang, China
- Center for Genetic and Genomic Medicine, Zhejiang University School of Medicine First Affiliated HospitalHangzhou, Zhejiang, China
| | - Arthur Moss
- Department of Medicine(Cardiology), University of RochesterRochester, New York, USA
| | - Peikuan Cong
- Center for Genetic and Genomic Medicine, Zhejiang University School of Medicine First Affiliated HospitalHangzhou, Zhejiang, China
| | - Min Pan
- Center for Genetic and Genomic Medicine, Zhejiang University School of Medicine First Affiliated HospitalHangzhou, Zhejiang, China
| | - Bingxi Chang
- Peking Union Medical College HospitalBeijing, China
| | - Liangrong Zheng
- Department of Cardiology, Zhejiang University School of Medicine First Affiliated HospitalHangzhou, Zhejiang, China
| | - Quan Fang
- Peking Union Medical College HospitalBeijing, China
| | - Wojciech Zareba
- Department of Medicine(Cardiology), University of RochesterRochester, New York, USA
| | - Jennifer Robinson
- Department of Medicine(Cardiology), University of RochesterRochester, New York, USA
| | - Changsong Lin
- Center for Genetic and Genomic Medicine, Zhejiang University School of Medicine First Affiliated HospitalHangzhou, Zhejiang, China
| | - Zhongxiang Li
- Zhejiang Academy of Medical SciencesHangzhou, Zhejiang, China
| | - Junfang Wei
- Division of Sport Medicine, College of Education, Zhejiang UniversityHangzhou, Zhejiang, China
| | | | - Ming Qi
- James D. Watson Institute of Genome Sciences, College of Life Sciences, Zhejiang UniversityHangzhou, Zhejiang, China
- Center for Genetic and Genomic Medicine, Zhejiang University School of Medicine First Affiliated HospitalHangzhou, Zhejiang, China
- Department of Pathology and Laboratory Medicine, University of RochesterRochester, New York, USA
- **Correspondence to Ming Qi, PhD, FACMG, Center for Genetic and Genomic Medicine, Zhejiang University School of Medicine First Affiliated Hospital, 79 Qingchun Road, Hangzhou, Zhejiang, China, 310003, Telephone: +86-571-88208274, Fax: +86-571-88208274, E-mail:
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Chattha IS, Sy RW, Yee R, Gula LJ, Skanes AC, Klein GJ, Bennett MT, Krahn AD. Utility of the recovery electrocardiogram after exercise: a novel indicator for the diagnosis and genotyping of long QT syndrome? Heart Rhythm 2010; 7:906-11. [DOI: 10.1016/j.hrthm.2010.03.006] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2010] [Accepted: 03/03/2010] [Indexed: 11/28/2022]
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Graff C, Struijk JJ, Matz J, Kanters JK, Andersen MP, Nielsen J, Toft E. Covariate analysis of QTc and T-wave morphology: new possibilities in the evaluation of drugs that affect cardiac repolarization. Clin Pharmacol Ther 2010; 88:88-94. [PMID: 20485337 DOI: 10.1038/clpt.2010.51] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This study adds the dimension of a T-wave morphology composite score (MCS) to the QTc interval-based evaluation of drugs that affect cardiac repolarization. Electrocardiographic recordings from 62 subjects on placebo and 400 mg moxifloxacin were compared with those from 21 subjects on 160 and 320 mg D,L-sotalol. T-wave morphology changes, as assessed by DeltaMCS, are larger after 320 mg D,L-sotalol than after 160 mg D,L-sotalol; and the changes associated with 160 mg D,L-sotalol are, in turn, larger than those associated with moxifloxacin and placebo. Covariate analyses of DeltaQTc and DeltaMCS showed that changes in T-wave morphology are a significant effect of D,L-sotalol. By contrast, moxifloxacin was found to have no significant effect on T-wave morphology (DeltaMCS) at any given change in QTc. This study offers new insights into the repolarization behavior of a drug associated with low cardiac risk vs. one associated with a high risk and describes the added benefits of a T-wave MCS as a covariate to the assessment of the QTc interval.
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Affiliation(s)
- C Graff
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
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Graff C, Matz J, Christensen EB, Andersen MP, Kanters JK, Toft E, Pehrson S, Hardahl TB, Nielsen J, Struijk JJ. Quantitative analysis of T-wave morphology increases confidence in drug-induced cardiac repolarization abnormalities: evidence from the investigational IKr inhibitor Lu 35-138. J Clin Pharmacol 2010; 49:1331-42. [PMID: 19843657 DOI: 10.1177/0091270009344853] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
This study investigates repolarization changes induced by a new candidate drug to determine whether a composite electrocardiographic (ECG) measure of T-wave morphology could be used as a reliable marker to support the evidence of abnormal repolarization, which is indicated by QT interval prolongation. Seventy-nine healthy subjects were included in this parallel study. After a baseline day during which no drug was given, 40 subjects received an I(Kr)-blocking antipsychotic compound (Lu 35-138) on 7 consecutive days while 39 subjects received placebo. Resting ECGs were recorded and used to determine a combined measure of repolarization morphology (morphology combination score [MCS]), based on asymmetry, flatness, and notching. Replicate measurements were used to determine reliable change and study power for both measures. Lu 35-138 increased the QTc interval with corresponding changes in T-wave morphology as determined by MCS. For subjects taking Lu 35-138, T-wave morphology was a more reliable indicator of I(Kr) inhibition than QTcF (chi(2) = 20.3, P = .001). At 80% study power for identifying a 5-millisecond placebo-adjusted change from baseline for QTcF, the corresponding study power for MCS was 93%. As a covariate to the assessment of QT interval liability, MCS offered important additive information to the effect of Lu 35-138 on cardiac repolarization.
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Affiliation(s)
- Claus Graff
- Department of Health Science and Technology, Center for Sensory Motor Interaction, Aalborg University, Aalborg, Denmark.
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Hedley PL, Jørgensen P, Schlamowitz S, Wangari R, Moolman-Smook J, Brink PA, Kanters JK, Corfield VA, Christiansen M. The genetic basis of long QT and short QT syndromes: A mutation update. Hum Mutat 2009; 30:1486-511. [DOI: 10.1002/humu.21106] [Citation(s) in RCA: 318] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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Xue J, Gao W, Chen Y, Han X. Identify drug-induced T wave morphology changes by a cell-to-electrocardiogram model and validation with clinical trial data. J Electrocardiol 2009; 42:534-42. [PMID: 19700171 DOI: 10.1016/j.jelectrocard.2009.07.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2009] [Indexed: 10/20/2022]
Abstract
BACKGROUND Increase of repolarization heterogeneity has been identified as a major factor for drug-induced arrhythmia event like torsade de pointes. In recent years, there have been quite a few efforts for studying T wave morphology changes, hoping to identify more sensitive proarrhythmia electrocardiogram (ECG) biomarkers than QT interval. However, the associations among ECG morphologies and the repolarization heterogeneities are still not clear. METHOD A cell-to-ECG model has been built by our group to study relationship between multiple factors of ion channels on the heart tissue and ECG morphology changes measured on the torso. More specifically, we varied both transmural (from Epi to Endo myocardium layers) and apex-to-base heterogeneities by blocking rapid delayed rectifier potassium current (Ikr), slow delayed rectifier potassium current (Iks), and late sodium current (InaL) with different extents on Epi, M, and Endo myocardium. On ECG measurement part, the study was focused on some new morphology-related features including T-peak to T-end (TpTe) interval, T wave flatness, T wave symmetric, and T wave notch. Two types of transmural dispersion of repolarization (TDR) were created: global and localized heterogeneities. Vector magnitude and principal component-based composite leads were formed from multiple chest leads for robustness against large variation of individual lead due to placement and noise issues. Cross-correlation methods were used to determine the relationship of the new ECG morphology features with the heterogeneities. All the ECG morphology measurements were first analyzed with the cell-to-ECG model and then validated with previously acquired clinical trial ECG data (d-sotalol). RESULTS The results based on our cell-to-ECG model showed that the new TpTe interval of the composite signal based on V2, V3, and V4 leads has the correlation coefficients of 0.99 and 0.98 with the simulated global and localized TDR, respectively, highest among other tested ECG parameters. The combined T wave morphology score has the correlation coefficients of 0.98 and 0.92 with the simulated global and localized TDR, respectively. The validation results of d-sotalol show that new TpTe measurement has a correlation coefficient of 0.90 with plasma concentration, and the parameter's correlation with heart rate is 0.02. CONCLUSIONS The study provided preliminary results showing the usefulness of the cell-to-ECG model for studying relationship between multiple ion-channel factors with ECG morphology changes. The global and localized TDR generate very different T wave morphologies. The newly identified T wave morphology parameters are highly correlated with transmural dispersion and are heart rate independent.
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Affiliation(s)
- Joel Xue
- Diagnostic Cardiology, GE Healthcare, 9900 Innovation Drive, Wauwatosa, WI 53226, USA.
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Graff C, Andersen MP, Xue JQ, Hardahl TB, Kanters JK, Toft E, Christiansen M, Jensen HK, Struijk JJ. Identifying Drug-Induced Repolarization Abnormalities from Distinct ECG Patterns in Congenital Long QT Syndrome. Drug Saf 2009; 32:599-611. [DOI: 10.2165/00002018-200932070-00006] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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Couderc JP. Measurement and regulation of cardiac ventricular repolarization: from the QT interval to repolarization morphology. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2009; 367:1283-99. [PMID: 19324709 PMCID: PMC2635501 DOI: 10.1098/rsta.2008.0284] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Ventricular repolarization (VR) is a crucial step in cardiac electrical activity because it corresponds to a recovery period setting the stage for the next heart contraction. Small perturbations of the VR process can predispose an individual to lethal arrhythmias. In this review, I aim to provide an overview of the methods developed to analyse static and dynamic aspects of the VR process when recorded from a surface electrocardiogram (ECG). The first section describes the list of physiological and clinical factors that can affect the VR. Technical aspects important to consider when digitally processing ECGs are provided as well. Special attention is given to the analysis of the effect of heart rate on the VR and its regulation by the autonomic nervous system. The final section provides the rationale for extending the analysis of the VR from its duration to its morphology. Several modelling techniques and measurement methods will be presented and their role within the arena of cardiac safety will be discussed.
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Affiliation(s)
- Jean-Philippe Couderc
- Heart Research Follow-Up Program, Cardiology Department, Box 653, University of Rochester Medical Center, 601 Elmwood Avenue, University of Rochester, Rochester, NY 14642, USA.
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Kanters JK, Haarmark C, Vedel-Larsen E, Andersen MP, Graff C, Struijk JJ, Thomsen PEB, Christiansen M, Jensen HK, Toft E. TpeakTend interval in long QT syndrome. J Electrocardiol 2008; 41:603-8. [DOI: 10.1016/j.jelectrocard.2008.07.024] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2008] [Revised: 07/04/2008] [Accepted: 07/05/2008] [Indexed: 12/17/2022]
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Couderc JP, Zhou M, Sarapa N, Zareba W. Investigating the effect of sotalol on the repolarization intervals in healthy young individuals. J Electrocardiol 2008; 41:595-602. [DOI: 10.1016/j.jelectrocard.2008.06.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2008] [Revised: 06/24/2008] [Accepted: 06/25/2008] [Indexed: 10/21/2022]
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New descriptors of T-wave morphology are independent of heart rate. J Electrocardiol 2008; 41:557-61. [DOI: 10.1016/j.jelectrocard.2008.07.021] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2008] [Revised: 06/26/2008] [Accepted: 07/02/2008] [Indexed: 11/29/2022]
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35
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Kanters JK, Graff C, Andersen MP, Hardahl T, Toft E, Christiansen M, Bloch Thomsen PE, Struijk JJ. Long QT syndrome genotyping by electrocardiography: fact, fiction, or something in between? J Electrocardiol 2006; 39:S119-22. [PMID: 16920146 DOI: 10.1016/j.jelectrocard.2006.06.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2006] [Revised: 06/06/2006] [Accepted: 06/13/2006] [Indexed: 12/19/2022]
Abstract
Diagnosis of long QT syndrome (LQTS) is difficult. A prolonged QT interval is easily overlooked, and in 10% of all patients with LQTS, the QT interval is normal. Genotyping is unfortunately not able to detect all patients and healthy subjects correctly. Although QT prolongation is the most used risk parameter, there is no clear correlation between the prolonged QT interval and the risk of arrhythmias in drug-induced LQTS. Quantification of T-wave morphology is a promising method that is able to provide more information about repolarization than QT prolongation alone. It is a fact that ECG evaluation can serve as a guide for genotyping and can reduce the costs by suggesting which gene to start sequencing, but it is fiction that the ECG can replace genotyping.
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Affiliation(s)
- Jørgen K Kanters
- Laboratory of Experimental Cardiology, Department of Medical Physiology, University of Copenhagen, DK2200 Copenhagen N, Denmark.
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