QT interval variability and adaptation to heart rate changes in patients with long QT syndrome

Jan Němec, Marie Buncová, Vladimir Shusterman, Bruce Winter, Win Kuang Shen, Michael John Ackerman

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Background: Increased QT variability (QTV) has been reported in conditions associated with ventricular arrhythmias. Data on QTV in patients with congenital long QT syndrome (LQTS) are limited. Methods: Ambulatory electrocardiogram recordings were analyzed in 23 genotyped LQTS patients and in 16 healthy subjects (C). Short-term QTV was compared between C and LQTS. The dependence of QT duration on heart rate was evaluated with three different linear models, based either on the RR interval preceding the QT interval (RR0), the RR interval preceding RR0 (RR-1), or the average RR interval in the 60-second period before QT interval (mRR). Results: Short-term QTV was significantly higher in LQTS than in C subjects (14.94 ± 9.33 vs 7.31 ± 1.29 ms; P < 0.001). It was also higher in the non-LQT1 than in LQT1 patients (23.00 ± 9.05 vs 8.74 ± 1.56 ms; P < 0.001) and correlated positively with QTc in LQTS (r = 0.623, P < 0.002). In the C subjects, the linear model based on mRR predicted QT duration significantly better than models based on RR0 and RR-1. It also provided better fit than any nonlinear model based on RR0. This was also true for LQT1 patients. For non-LQT1 patients, all models provided poor prediction of QT interval. Conclusions: QTV is elevated in LQTS patients and is correlated with QTc in LQTS. Significant differences with respect to QTV exist among different genotypes. QT interval duration is strongly affected by noninstantaneous heart rate in both C and LQT1 subjects. These findings could improve formulas for QT interval correction and provide insight on cellular mechanisms of QT adaptation.

Original languageEnglish (US)
Pages (from-to)72-81
Number of pages10
JournalPACE - Pacing and Clinical Electrophysiology
Volume32
Issue number1
DOIs
StatePublished - Jan 2009

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Long QT Syndrome
Heart Rate
Linear Models
Nonlinear Dynamics
Cardiac Arrhythmias
Healthy Volunteers
Electrocardiography
Genotype

Keywords

  • Long QT syndrome
  • QT correction
  • QT variability

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

QT interval variability and adaptation to heart rate changes in patients with long QT syndrome. / Němec, Jan; Buncová, Marie; Shusterman, Vladimir; Winter, Bruce; Shen, Win Kuang; Ackerman, Michael John.

In: PACE - Pacing and Clinical Electrophysiology, Vol. 32, No. 1, 01.2009, p. 72-81.

Research output: Contribution to journalArticle

Němec, Jan ; Buncová, Marie ; Shusterman, Vladimir ; Winter, Bruce ; Shen, Win Kuang ; Ackerman, Michael John. / QT interval variability and adaptation to heart rate changes in patients with long QT syndrome. In: PACE - Pacing and Clinical Electrophysiology. 2009 ; Vol. 32, No. 1. pp. 72-81.
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abstract = "Background: Increased QT variability (QTV) has been reported in conditions associated with ventricular arrhythmias. Data on QTV in patients with congenital long QT syndrome (LQTS) are limited. Methods: Ambulatory electrocardiogram recordings were analyzed in 23 genotyped LQTS patients and in 16 healthy subjects (C). Short-term QTV was compared between C and LQTS. The dependence of QT duration on heart rate was evaluated with three different linear models, based either on the RR interval preceding the QT interval (RR0), the RR interval preceding RR0 (RR-1), or the average RR interval in the 60-second period before QT interval (mRR). Results: Short-term QTV was significantly higher in LQTS than in C subjects (14.94 ± 9.33 vs 7.31 ± 1.29 ms; P < 0.001). It was also higher in the non-LQT1 than in LQT1 patients (23.00 ± 9.05 vs 8.74 ± 1.56 ms; P < 0.001) and correlated positively with QTc in LQTS (r = 0.623, P < 0.002). In the C subjects, the linear model based on mRR predicted QT duration significantly better than models based on RR0 and RR-1. It also provided better fit than any nonlinear model based on RR0. This was also true for LQT1 patients. For non-LQT1 patients, all models provided poor prediction of QT interval. Conclusions: QTV is elevated in LQTS patients and is correlated with QTc in LQTS. Significant differences with respect to QTV exist among different genotypes. QT interval duration is strongly affected by noninstantaneous heart rate in both C and LQT1 subjects. These findings could improve formulas for QT interval correction and provide insight on cellular mechanisms of QT adaptation.",
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AB - Background: Increased QT variability (QTV) has been reported in conditions associated with ventricular arrhythmias. Data on QTV in patients with congenital long QT syndrome (LQTS) are limited. Methods: Ambulatory electrocardiogram recordings were analyzed in 23 genotyped LQTS patients and in 16 healthy subjects (C). Short-term QTV was compared between C and LQTS. The dependence of QT duration on heart rate was evaluated with three different linear models, based either on the RR interval preceding the QT interval (RR0), the RR interval preceding RR0 (RR-1), or the average RR interval in the 60-second period before QT interval (mRR). Results: Short-term QTV was significantly higher in LQTS than in C subjects (14.94 ± 9.33 vs 7.31 ± 1.29 ms; P < 0.001). It was also higher in the non-LQT1 than in LQT1 patients (23.00 ± 9.05 vs 8.74 ± 1.56 ms; P < 0.001) and correlated positively with QTc in LQTS (r = 0.623, P < 0.002). In the C subjects, the linear model based on mRR predicted QT duration significantly better than models based on RR0 and RR-1. It also provided better fit than any nonlinear model based on RR0. This was also true for LQT1 patients. For non-LQT1 patients, all models provided poor prediction of QT interval. Conclusions: QTV is elevated in LQTS patients and is correlated with QTc in LQTS. Significant differences with respect to QTV exist among different genotypes. QT interval duration is strongly affected by noninstantaneous heart rate in both C and LQT1 subjects. These findings could improve formulas for QT interval correction and provide insight on cellular mechanisms of QT adaptation.

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