Literature DB >> 30571576

Determination and Interpretation of the QT Interval.

Arja Suzanne Vink1,2, Benjamin Neumann3, Krystien V V Lieve1, Moritz F Sinner3,4, Nynke Hofman1, Soufiane El Kadi1, Melissa H A Schoenmaker1, Hanneke M J Slaghekke1, Jonas S S G de Jong5, Sally-Ann B Clur2, Nico A Blom2,6, Stefan Kääb3,7, Arthur A M Wilde1,4, Pieter G Postema1.   

Abstract

BACKGROUND: Long QT syndrome (LQTS) is associated with potentially fatal arrhythmias. Treatment is very effective, but its diagnosis may be challenging. Importantly, different methods are used to assess the QT interval, which makes its recognition difficult. QT experts advocate manual measurements with the tangent or threshold method. However, differences between these methods and their performance in LQTS diagnosis have not been established. We aimed to assess similarities and differences between these 2 methods for QT interval analysis to aid in accurate QT assessment for LQTS.
METHODS: Patients with a confirmed pathogenic variant in KCNQ1(LQT1), KCNH2(LQT2), or SCN5A(LQT3) genes and their family members were included. Genotype-positive patients were identified as LQTS cases and genotype-negative family members as controls. ECGs were analyzed with both methods, providing inter- and intrareader validity and diagnostic accuracy. Cutoff values based on control population's 95th and 99th percentiles, and LQTS-patients' 1st and 5th percentiles were established based on the method to correct for heart rate, age, and sex.
RESULTS: We included 1484 individuals from 265 families, aged 33±21 years and 55% females. In the total cohort, QTTangent was 10.4 ms shorter compared with QTThreshold (95% limits of agreement±20.5 ms, P<0.0001). For all genotypes, QTTangent was shorter than QTThreshold ( P<0.0001), but this was less pronounced in LQT2. Both methods yielded a high inter- and intrareader validity (intraclass correlation coefficient >0.96), and a high diagnostic accuracy (area under the curve >0.84). Using the current guideline cutoff (QTc interval 480 ms), both methods had similar specificity but yielded a different sensitivity. QTc interval cutoff values of QTTangent were lower compared with QTThreshold and different depending on the correction for heart rate, age, and sex.
CONCLUSION: The QT interval varies depending on the method used for its assessment, yet both methods have a high validity and can both be used in diagnosing LQTS. However, for diagnostic purposes current guideline cutoff values yield different results for these 2 methods and could result in inappropriate reassurance or treatment. Adjusted cutoff values are therefore specified for method, correction formula, age, and sex. In addition, a freely accessible online probability calculator for LQTS ( www.QTcalculator.org ) has been made available as an aid in the interpretation of the QT interval.

Entities:  

Keywords:  long QT syndrome

Mesh:

Substances:

Year:  2018        PMID: 30571576     DOI: 10.1161/CIRCULATIONAHA.118.033943

Source DB:  PubMed          Journal:  Circulation        ISSN: 0009-7322            Impact factor:   29.690


  29 in total

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5.  Diagnostic Yield of Genetic Testing in Young Patients With Atrioventricular Block of Unknown Cause.

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7.  Dynamic QT response to cold-water face immersion in long-QT syndrome type 3.

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9.  Diagnostic accuracy of the response to the brief tachycardia provoked by standing in children suspected for long QT syndrome.

Authors:  Arja S Vink; Ben J M Hermans; Joana Pimenta; Puck J Peltenburg; Luc H P M Filippini; Nynke Hofman; Sally-Ann B Clur; Nico A Blom; Arthur A M Wilde; Tammo Delhaas; Pieter G Postema
Journal:  Heart Rhythm O2       Date:  2021-03-13

10.  Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome.

Authors:  Najim Lahrouchi; Rafik Tadros; Lia Crotti; Yuka Mizusawa; Pieter G Postema; Leander Beekman; Roddy Walsh; Kanae Hasegawa; Julien Barc; Marko Ernsting; Kari L Turkowski; Andrea Mazzanti; Britt M Beckmann; Keiko Shimamoto; Ulla-Britt Diamant; Yanushi D Wijeyeratne; Yu Kucho; Tomas Robyns; Taisuke Ishikawa; Elena Arbelo; Michael Christiansen; Annika Winbo; Reza Jabbari; Steven A Lubitz; Johannes Steinfurt; Boris Rudic; Bart Loeys; M Ben Shoemaker; Peter E Weeke; Ryan Pfeiffer; Brianna Davies; Antoine Andorin; Nynke Hofman; Federica Dagradi; Matteo Pedrazzini; David J Tester; J Martijn Bos; Georgia Sarquella-Brugada; Óscar Campuzano; Pyotr G Platonov; Birgit Stallmeyer; Sven Zumhagen; Eline A Nannenberg; Jan H Veldink; Leonard H van den Berg; Ammar Al-Chalabi; Christopher E Shaw; Pamela J Shaw; Karen E Morrison; Peter M Andersen; Martina Müller-Nurasyid; Daniele Cusi; Cristina Barlassina; Pilar Galan; Mark Lathrop; Markus Munter; Thomas Werge; Marta Ribasés; Tin Aung; Chiea C Khor; Mineo Ozaki; Peter Lichtner; Thomas Meitinger; J Peter van Tintelen; Yvonne Hoedemaekers; Isabelle Denjoy; Antoine Leenhardt; Carlo Napolitano; Wataru Shimizu; Jean-Jacques Schott; Jean-Baptiste Gourraud; Takeru Makiyama; Seiko Ohno; Hideki Itoh; Andrew D Krahn; Charles Antzelevitch; Dan M Roden; Johan Saenen; Martin Borggrefe; Katja E Odening; Patrick T Ellinor; Jacob Tfelt-Hansen; Jonathan R Skinner; Maarten P van den Berg; Morten Salling Olesen; Josep Brugada; Ramón Brugada; Naomasa Makita; Jeroen Breckpot; Masao Yoshinaga; Elijah R Behr; Annika Rydberg; Takeshi Aiba; Stefan Kääb; Silvia G Priori; Pascale Guicheney; Hanno L Tan; Christopher Newton-Cheh; Michael J Ackerman; Peter J Schwartz; Eric Schulze-Bahr; Vincent Probst; Minoru Horie; Arthur A Wilde; Michael W T Tanck; Connie R Bezzina
Journal:  Circulation       Date:  2020-05-20       Impact factor: 39.918

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