Giant U waves: an important clinical clue

Verma, Nitin; Figueredo, Vincent M.; Greenspan, Allan M.; Pressman, Gregg

doi:10.2147/rrcc.s18459

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…Our study demonstrates unequivocally that U waves are observable at elevated heart rates. According to the literature, only very rarely can U waves be observed in subjects with heart rates above 90 bpm [ 1 , 6 , 7 , 8 ]. In our study, the average post-exercise heart rate was 100 bpm and 17 of 20 subjects had heart rates greater than 90 bpm, yet we could readily observe U waves in all subjects.…”

Section: Discussionmentioning

confidence: 99%

“…Surawicz stated that U waves could be observed in 90% of cases when the heart rate is less than 65 bpm, while they are observed in only 25% of cases when the heart rate is 80 to 90 bpm, and are rarely detectable when the heart rate exceeds 95 bpm [ 1 ]. Other authors have reasserted this claim [ 6 , 7 , 8 ]. It is unclear if the reason for not being able to detect U waves at high heart rates was due to mechanistic reasons (i.e., U waves are not generated at high heart rates) or if they were undetectable due to technical reasons, such as being obscured by contaminating noise or P waves of the following beat.…”

Section: Introductionmentioning

confidence: 92%

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Multi-Beat Averaging Reveals U Waves Are Ubiquitous and Standing Tall at Elevated Heart Rates Following Exercise

Al-Karadi

Langley

2020

Sensors

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The reporting of U wave abnormalities is clinically important, but the measurement of this small electrocardiographic (ECG) feature is extremely difficult, especially in challenging recording conditions, such as stress exercise, due to contaminating noise. Furthermore, it is widely stated that ECG U waves are rarely observable at heart rates greater than 90 bpm. The aims of the study were (i) to assess the ability of multi-beat averaging to reveal the presence of U waves in ECGs contaminated by noise following exercise and (ii) to quantify the effect of exercise on U wave amplitude. The multi-beat averaging algorithm was applied to recover U waves in 20 healthy subjects in pre- and post-exercise recordings. Average beats were generated from 30 beat epochs. The prevalence of U waves and their amplitudes were measured in pre- and post-exercise recordings and changes in amplitude due to exercise were quantified. U waves were present in all subjects in pre-exercise recordings. Following exercise, U waves could not be seen in standard ECG but were observable in all 20 subjects by multi-beat averaging and despite significantly increased mean (±SD) heart rate (63 ± 8 bpm vs. 100 ± 9 bpm, p < 0.0001). Furthermore, U waves were observable in all subjects with heart rates greater than 90 bpm. U waves significantly increased in amplitude following exercise (38 ± 15 μV vs. 80 ± 48 μV, p = 0.0005). Multi-beat averaging is effective at recovering U waves contaminated by noise due to exercise. U waves were measurable in all subjects, dispelling the myth that U waves are rarely seen at elevated heart rates. U waves exhibit increased amplitudes at elevated heart rates following exercise.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Multi-Beat Averaging Reveals U Waves Are Ubiquitous and Standing Tall at Elevated Heart Rates Following Exercise

Al-Karadi

Langley

2020

Sensors

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“…The results after removing the P-wave and PR interval are represented as X[n]. A normal U-wave has an amplitude of less than one-fourth of the T-wave (Verma et al 2011) and rarely exceeds 0.2 mV. Hence, the T-wave peak is considered the most prominent wave in X[n].…”

Section: Baseline Identificationmentioning

confidence: 99%

Improved T-wave detection in electrocardiogram signals based non-stationary wavelet transform and QRS complex cancellation with kurtosis analysis

Sharma,

Sunkaria

2023

Physiol. Meas.

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Objective: The T-wave in electrocardiogram (ECG) signal has the potential to enumerate various cardiac dysfunctions in the cardiovascular system. The primary objective of this research is to develop an efficient method for detecting T-waves in ECG signals, with potential applications in clinical diagnosis and continuous patient monitoring. Approach: In this work, we propose a novel algorithm for T-wave peak detection, which relies on a Non-decimated stationary wavelet transform method (NSWT) and involves the cancellation of the QRS complex by utilizing its local extrema. The proposed scheme contains three stages: Firstly, the technique is pre-processed using a two-stage median filter and Savitzky-Golay (SG) filter to remove the various artifacts from the ECG signal. Secondly, the NSWT technique is implemented using the bior 4.4 mother wavelet without downsampling, employing 24 scale analysis, and involves the cancellation of QRS-complex using its local positions. After that, Sauvola technique is used to estimate the baseline and remove the P-wave peaks to enhance T-peaks for accurate detection in the ECG signal. Additionally, the moving average window and adaptive thresholding are employed to enhance and identify the location of the T-wave peaks. Thirdly, false positive T-peaks are corrected using the kurtosis coefficients method.Main results: The robustness and efficiency of the proposed technique have been corroborated by the QT database (QTDB). The results are also validated on a self-recorded database. In QTDB database, the sensitivity of 98.20%, positive predictivity of 99.82%, accuracy of 98.04%, and detection error rate of 1.95% have been achieved. The self-recorded dataset attains a sensitivity, positive predictivity, accuracy, and detection error rate of 99.94%, 99.96%, 99.90%, and 0.09% respectively.Significance: A T-wave peak detection based on NSWT and QRS complex cancellation, along with kurtosis analysis technique, demonstrates superior performance and enhanced detection accuracy compared to state-of-the-art techniques. 

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ST-elevation and non-ST-elevation acute coronary syndromes: Should the guidelines be changed?

Gorgels

2013

Journal of Electrocardiology

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Giant U waves: an important clinical clue

Cited by 3 publications

References 26 publications

Multi-Beat Averaging Reveals U Waves Are Ubiquitous and Standing Tall at Elevated Heart Rates Following Exercise

Multi-Beat Averaging Reveals U Waves Are Ubiquitous and Standing Tall at Elevated Heart Rates Following Exercise

Improved T-wave detection in electrocardiogram signals based non-stationary wavelet transform and QRS complex cancellation with kurtosis analysis

ST-elevation and non-ST-elevation acute coronary syndromes: Should the guidelines be changed?

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