Literature DB >> 11333172

Improving the reproducibility of QT dispersion measures.

K Lund1, J S Perkiömäki, C Brohet, M Zaïdi, H Elming, C T Pedersen, H V Huikuri, H Nygaard, A K Pedersen.   

Abstract

BACKGROUND: The low reproducibility of the QT dispersion (QTD) method is a major reason why it is not used in clinics. The purpose of this study was to develop QT dispersion parameters with better reproducibility and identification of patients with a high risk of ventricular arrhythmia or death. METHODS AND
RESULTS: Three institutions using different methods for measuring QT intervals provided QT databases, which included more than 3500 twelve-lead surface ECGs. The data represented low and high risk subjects from the following groups: the normal population EpiSet (survivors vs dead from cardiovascular causes), acute myocardial infarction patients AmiSet (survivors vs dead) and remote myocardial infarction patients ArrSet (with vs without a history of ventricular arrhythmia). The EpiSet, AmiSet, and the ArrSet contributed with N = 122, 0, and 110 ECGs for reproducibility analysis, and 3244, 446, and 100 ECGs for the analysis of prognostic accuracy. The prognostic accuracy was measured as the area under the Receiver Operator Curve. The QT intervals were divided into six QT pairs; the longest pair consisted of the longest and the shortest QT intervals etc. The QT dispersion trend (QTDT) was defined as the slope of the linear regression of the N longest QT pairs after estimation of missing QT intervals by interpolation of measured QT intervals. The QTMAD and the QTSTD methods were defined as twice the mean absolute deviation and the standard deviation of the N longest QT pairs. The reproducibility was improved by 27% and 19% in the EpiSet and the ArrSet relative to the reproducibility of QTD. The accuracy improved for the EpiSet and the ArrSet and was maintained for the AmiSet.
CONCLUSIONS: By using the three longest and the three shortest QT intervals in QTDT, QTMAD, or QTSTD, the reproducibility improved significantly while maintaining or improving the prognostic accuracy compared to QTD.

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Mesh:

Year:  2001        PMID: 11333172      PMCID: PMC7027631          DOI: 10.1111/j.1542-474x.2001.tb00099.x

Source DB:  PubMed          Journal:  Ann Noninvasive Electrocardiol        ISSN: 1082-720X            Impact factor:   1.468


  19 in total

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Journal:  Eur Heart J       Date:  1991-03       Impact factor: 29.983

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Authors:  M Zabel; R L Woosley; M R Franz
Journal:  Pacing Clin Electrophysiol       Date:  1997-10       Impact factor: 1.976

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Authors:  J Kautzner; M Malik
Journal:  Pacing Clin Electrophysiol       Date:  1997-10       Impact factor: 1.976

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Journal:  J Cardiovasc Electrophysiol       Date:  1994-08

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Authors:  J S Perkiömäki; H V Huikuri; J M Koistinen; T Mäkikallio; A Castellanos; R J Myerburg
Journal:  J Am Coll Cardiol       Date:  1997-11-01       Impact factor: 24.094

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Authors:  K Lund; H Arildsen; J S Perkiömäki; H V Huikuri; O May; A K Pedersen
Journal:  Ann Noninvasive Electrocardiol       Date:  2001-01       Impact factor: 1.468

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Journal:  Br Heart J       Date:  1994-06

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Authors:  J S Perkiömäki; M J Koistinen; S Yli-Mäyry; H V Huikuri
Journal:  J Am Coll Cardiol       Date:  1995-07       Impact factor: 24.094

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Journal:  Br Heart J       Date:  1995-01

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  2 in total

1.  Weighing the QT intervals with the slope or the amplitude of the T wave.

Authors:  Kaspar Lund; Hans Nygaard; Anders Kirstein Pedersen
Journal:  Ann Noninvasive Electrocardiol       Date:  2002-01       Impact factor: 1.468

2.  The prognostic accuracy of different QT interval measures.

Authors:  Kaspar Lund; Juha S Perkiömäki; Christian Brohet; Hanne Elming; Mohammed Zaïdi; Christian Torp-Pedersen; Heikki V Huikuri; Hans Nygaard; Anders Kirstein Pedersen
Journal:  Ann Noninvasive Electrocardiol       Date:  2002-01       Impact factor: 1.468

  2 in total

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