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Cited by 1,189

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QT dispersion: an indication of arrhythmia risk in patients with long QT intervals.

Open access
Day, C P, McComb, J M, Campbell, R W·1990·Heart

Abstract

Homogeneity of recovery time protects against arrhythmias whereas dispersion of recovery time is arrhythmogenic. A single surface electrocardiographic QT interval gives no information on recovery time dispersion but the difference between the maximum and minimum body surface QT interval may be relevant. This hypothesis was tested by measuring the dispersion of the corrected QT interval (QTc) in 10 patients with an arrhythmogenic long QT interval (Romano Ward and Jervell and Lange-Nielsen syndromes or drug arrhythmogenicity) and in 14 patients without arrhythmias in whom the QT interval was prolonged by sotalol. QTc dispersion was significantly greater in the arrhythmogenic QT group than in the sotalol QT group. In patients with prolonged QT intervals, QT dispersion distinguished between those with ventricular arrhythmias and those without. This supports the hypothesis that QT dispersion reflects spatial differences in myocardial recovery time. QT dispersion may be useful in the assessment of both arrhythmia risk and the efficacy of antiarrhythmic drugs.

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Metadata

Authors
Day, C. P., McComb, J. M., & Campbell, R. W.
Venue
Heart
Publisher
BMJ
Published
1990-06-01
Volume
63
Issue
6
Pages
342-344
ISSN
1355-6037 (ISSN-L)
OpenAlex
W2161999690
Cited by
1,189
References
0
FWCI
7.34
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: QT dispersion: an indication of arrhythmia risk in patients with long QT intervals. https://app.cochat.ai/papers/10.1136/hrt.63.6.342
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Day, C. P., McComb, J. M., & Campbell, R. W. (1990). QT dispersion: an indication of arrhythmia risk in patients with long QT intervals. Heart. https://doi.org/10.1136/hrt.63.6.342

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.