Measurement and Rate Correction of the QT Interval

Pickham, David; Hasanien, Amer A.

doi:10.1097/nci.0b013e318274ba3e

Cited by 12 publications

(6 citation statements)

References 34 publications

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“…Measures of cardiac repolarization were determined as indicated in Figure 1. The QT interval was defined as the time from the earliest onset of the QRS complex to the end of the T wave [22]. The end of the T wave was defined as the cutting point of the tangent to the downward slope of the T-wave and the isoelectric line [23].…”

Section: Methodsmentioning

confidence: 99%

High prevalence of altered cardiac repolarization in patients with COPD

et al. 2014

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BackgroundAltered cardiac repolarization and increased dispersion of repolarization have been identified as risk factors for sudden cardiac death (SCD). The prevalence of and the mechanisms contributing to altered cardiac repolarization are currently unknown in COPD.MethodsIn 91 COPD patients, 32 controls matched for age, cardiovascular risk and medication, and 41 healthy subjects, measures of cardiac repolarization and dispersion of repolarization (QTc interval, QT dispersion) were derived from 12-lead electrocardiography (ECG). Prevalence rates of heart rate corrected QT (QTc) >450ms and QT dispersion >60ms were determined to assess the number of subjects at risk for SCD. Univariate and multivariate analyses were used to identify possible factors contributing to altered cardiac repolarization.ResultsQTc was found to be prolonged in 31.9% and QT dispersion in 24.2% of the COPD patients compared to 12.5% in matched controls and 0% in healthy subjects. The QTc interval was longer in COPD patients compared to matched and healthy controls respectively (437.9 ± 29.5 vs. 420.1 ± 25.3 ms, p = 0.001 and vs. 413.4 ± 18.2 ms, p < 0.001). QT dispersion was significantly increased in COPD patients compared to healthy subjects (45.4 (34.8 , 59.5) vs. 39.7 (29.3 , 54.8) ms, p = 0.049). Only oxygen saturation was independently associated with QTc duration in multivariate analysis (β = -0.29, p = 0.015).ConclusionOne third of a typical COPD population has altered cardiac repolarization and increased dispersion of repolarization, which may be related to hypoxia. Altered cardiac repolarization may expose these patients to an increased risk for malignant ventricular arrhythmias and SCD.

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Section: Methodsmentioning

confidence: 99%

High prevalence of altered cardiac repolarization in patients with COPD

et al. 2014

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“…For detailed discussion on measurement issues related to identifying the QRS onset or T wave end, see Pickham and Hasanien. 12 We have just read that the QRS complex represents ventricular depolarization, so why do we include the QRS complex in a measurement of ventricular repolarization? As a wave of depolarization flows through the ventricles, the recently depolarized cells immediately begin to repolarize.…”

Section: Magnitudementioning

confidence: 99%

Understanding and Documenting QT Intervals

Pickham

2013

Critical Care Nurse

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“…QT interval is inversely proportional to heart rate, which means that the QT shortens at faster heart rate and lengthens at slower heart rate. Therefore, after the QT interval has been measured, it must be mathematically corrected upon the heart rate [7,8]. The heart rate can be defined as the time between two successive ventricular depolarizations or R-to-R peak interval.…”

Section: Introductionmentioning

confidence: 99%

Automated QT Interval Measurement Using Modified Pan-Tompkins Algorithm with Independent Isoelectric Line Approach

Jumahat

Beng

Misran

et al. 2020

JBBBE

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The QT interval on the electrocardiogram (ECG) signal is known to have an important role in monitoring heart’s electrical activity because the presence of QT interval prolongation can be associated with life-threatening cardiac events. This interval can be identified and measured using either manual or automated techniques. Currently, studies on automated QT interval measurement algorithms are becoming a growing field, as they can provide the best solution to overcome misdiagnosis and timely issues resulting from manual identification. However, the physiological variability of the QRS complex and the fluctuation of the isoelectric line are prevalent issues that need to be considered in the automatic method. In this report, an algorithm to identify the QRS onset and T-wave offset for measuring the corrected QT interval (QTc) is proposed. This method uses an improved Pan-Tompkins algorithm from the previous work with independent of the isoelectric line approach for detecting the QRS onset and the T offset. The algorithm was implemented in Matlab and applied to the 60 seconds duration of 27 records in the PPUKM database with a sampling frequency of 500 Hz. The performance of the algorithm achieved a sensitivity of 100% for QRS onset detection and 100% for T offset detection. As for the accuracy, the algorithm’s performance obtained 100% for QRS onset detection and 99.56% for T offset detection. The mean error results with respect to manual annotation were 37±18.5 ms for QRS onset detection and 32±22.3 ms for T offset detection which was within ANSI/AAMI-EC57:1998 standard tolerance. The proposed algorithm exhibits reliable automated QTc measurement. Besides insensitive to morphological variations of ECG waves, the computational method is simple and possibly implemented as the basis for future software development for portable device applications.

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Measurement and Rate Correction of the QT Interval

Cited by 12 publications

References 34 publications

High prevalence of altered cardiac repolarization in patients with COPD

High prevalence of altered cardiac repolarization in patients with COPD

Understanding and Documenting QT Intervals

Automated QT Interval Measurement Using Modified Pan-Tompkins Algorithm with Independent Isoelectric Line Approach

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