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Assessment of the QT interval in the electroencephalography (EEG) of children with syncope, epilepsy, and attention-deficit hyperactivity disorder (ADHD)
Journal article   Peer reviewed

Assessment of the QT interval in the electroencephalography (EEG) of children with syncope, epilepsy, and attention-deficit hyperactivity disorder (ADHD)

Om P Jha, Divya S Khurana, Karen S Carvalho, Joseph J Melvin, Agustin Legido, Anna C O'Riordan and Ignacio Valencia
Journal of child neurology, v 25(3)
Mar 2010
PMID: 19713554

Abstract

Attention Deficit Disorder with Hyperactivity - epidemiology Attention Deficit Disorder with Hyperactivity - physiopathology Brain - physiopathology Child Databases, Factual Electrocardiography - methods Electroencephalography - methods Epilepsy - epidemiology Epilepsy - physiopathology Female Humans Incidence Male Pilot Projects Seizures - physiopathology Signal Processing, Computer-Assisted Syncope - epidemiology Syncope - physiopathology Time Factors
The interpretation of QT interval is often neglected during electroencephalography (EEG) reading. We compared the incidence of prolonged QT interval, as seen in the electrocardiography (ECG) recording lead of the EEG, in children presenting with seizure, syncope, or attention-deficit hyperactivity disorder (ADHD). Abnormal QT was defined as >460 ms. The incidence of prolonged QT in the seizure, syncope, and ADHD groups was 1/50 (2%), 7/50 (14%), and 2/50 (4%), respectively (P = .036, chi-square). The mean +/- SD of QT were 405 +/- 34, 424 +/- 39, and 414 +/- 36, respectively (P = .035, analysis of variance [ANOVA], syncope group, compared with seizure group). The incidence of prolonged QT as measured in the EEG was unexpectedly high in children presenting with seizure, syncope, or ADHD. These data support the concept that QT evaluation should be emphasized during routine EEG reading, as it may aid in identifying cases of undiagnosed cardiac conduction abnormalities. Prospective studies comparing EEG-ECG tracings with 12-lead ECG are warranted.

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Web of Science research areas
Clinical Neurology
Pediatrics
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