Philips QT Interval Measurement Algorithms for Diagnostic, Ambulatory, and Patient Monitoring ECG Applications

Zhou, Sophia H.; Helfenbein, Eric; Lindauer, James M.; Gregg, Richard E.; Feild, Dirk Q.

doi:10.1111/j.1542-474x.2008.00258.x

Cited by 48 publications

(40 citation statements)

References 11 publications

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“…The most recent development is fully automated QTc monitoring, in which QT/QTc intervals are measured ev ery 5 minutes for display, alarms, and trending. 84,85 The fully automated method has the advantage of measur ing every QT interval from all monitoring leads and uses a representative heart rate for correction.…”

Section: Methods Used To Measure the Qtc Intervalmentioning

confidence: 99%

Update to Practice Standards for Electrocardiographic Monitoring in Hospital Settings: A Scientific Statement From the American Heart Association

Sandau¹,

Funk²,

Auerbach³

et al. 2017

Circulation

198

214

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Background and Purpose: This scientific statement provides an interprofessional, comprehensive review of evidence and recommendations for indications, duration, and implementation of continuous electro cardiographic monitoring of hospitalized patients. Since the original practice standards were published in 2004, new issues have emerged that need to be addressed: overuse of arrhythmia monitoring among a variety of patient populations, appropriate use of ischemia and QT-interval monitoring among select populations, alarm management, and documentation in electronic health records. Methods: Authors were commissioned by the American Heart Association and included experts from general cardiology, electrophysiology (adult and pediatric), and interventional cardiology, as well as a hospitalist and experts in alarm management. Strict adherence to the American Heart Association conflict of interest policy was maintained throughout the consensus process. Authors were assigned topics relevant to their areas of expertise, reviewed the literature with an emphasis on publications since the prior practice standards, and drafted recommendations on indications and duration for electrocardiographic monitoring in accordance with the American Heart Association Level of Evidence grading algorithm that was in place at the time of commissioning. Results: The comprehensive document is grouped into 5 sections: (1) Overview of Arrhythmia, Ischemia, and QTc Monitoring; (2) Recommendations for Indication and Duration of Electrocardiographic Monitoring presented by patient population; (3) Organizational Aspects: Alarm Management, Education of Staff, and Documentation; (4) Implementation of Practice Standards; and (5) Call for Research. Conclusions: Many of the recommendations are based on limited data, so authors conclude with specific questions for further research.

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Section: Methods Used To Measure the Qtc Intervalmentioning

confidence: 99%

Update to Practice Standards for Electrocardiographic Monitoring in Hospital Settings: A Scientific Statement From the American Heart Association

Sandau¹,

Funk²,

Auerbach³

et al. 2017

Circulation

198

214

View full text Add to dashboard Cite

show abstract

“…We have previously presented Philips automated QT interval measurement algorithms for 12-lead ECG, Holter and ECG monitoring applications [5][6][7][8][9][10]. In the ambulatory Holter and patient monitoring ECG applications, the QT interval algorithm uses an RMS waveform from combined available high quality leads and measures QT interval on the RMS ECG.…”

Section: Introductionmentioning

confidence: 99%

“…The AHA/ACC practice guideline for ECG monitoring now includes a recommendation to monitor QT interval for the purpose of drug titration of drugs known to have a pro-arrhythmic effect [4]. If the QT interval lengthens by more than 60ms after starting the drug or the QT interval extends beyond 500 ms the administration of the drug should be stopped or the dosage can be reduced.We have previously presented Philips automated QT interval measurement algorithms for 12-lead ECG, Holter and ECG monitoring applications [5][6][7][8][9][10]. In the ambulatory Holter and patient monitoring ECG applications, the QT interval algorithm uses an RMS waveform from combined available high quality leads and measures QT interval on the RMS ECG.…”

mentioning

confidence: 99%

Comparison of two automated methods for QT interval measurement

Gregg

Babaeizadeh

Feild

et al. 2007

2007 Computers in Cardiology

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In this paper we compared two methods of automated QT interval measurement on standard ECG databases: the Root-Mean-Square (RMS) lead combining method aimed at QT monitoring and the method of median of lead-by-lead QT interval measurements.We IntroductionGlobal QT interval is one of the fundamental ECG measurements reported on virtually every 12 lead ECG. A longer than normal QT interval may indicate a congenital or acquired long QT condition [1][2][3]. The AHA/ACC practice guideline for ECG monitoring now includes a recommendation to monitor QT interval for the purpose of drug titration of drugs known to have a pro-arrhythmic effect [4]. If the QT interval lengthens by more than 60ms after starting the drug or the QT interval extends beyond 500 ms the administration of the drug should be stopped or the dosage can be reduced.We have previously presented Philips automated QT interval measurement algorithms for 12-lead ECG, Holter and ECG monitoring applications [5][6][7][8][9][10]. In the ambulatory Holter and patient monitoring ECG applications, the QT interval algorithm uses an RMS waveform from combined available high quality leads and measures QT interval on the RMS ECG. In the resting 12-lead ECG application, the global QT interval measurement is based on a lead-by-lead method. The open question is, of the two, which method is better ignoring the constraints of the application. In this paper, we compared the two automated methods and reported the results using the same ECG datasets. Study PopulationA comparison between automated methods aimed at either monitoring or ambulatory ECG versus 12-lead ECG is hampered by the gross difference in available ECG in each case. Ambulatory ECGs cannot be used to test the 12-lead QT algorithm because of low sample rate, narrow bandwidth and limited leads. For 12-lead ECG analysis, a sample rate of 500 sps and a bandwidth of 0.05 to 150Hz are required. Ambulatory ECG recordings often have sample rates around 200 sps and a cut-off frequency of 40Hz. Only selected parts of the 12-lead analysis are possible with the small number of leads used in an ambulatory or monitoring recording. On the other hand, the sample rate, bandwidth and number of leads may be adequate for a 12-lead ECG to be used for an ambulatory analysis, but the 10 second recording is not long enough for even the learning period of the ambulatory and monitoring algorithmsThe addition of the PTB set to the data publicly available at PhysioNet made this study possible because it has the features that allow direct comparison between ambulatory and 12 lead algorithms [11]. The PTB dataset consists of 549 records from 294 subjects with a sample

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“…13,16 The monitors used in our NICU are designed to account for these difficulties and use a signal averaging and filter-based algorithm to measure the QTc more accurately and provide more stable trends. 3,17 Its use has been demonstrated previously to reliably and accurately measure QTc values compared with a cardiologist. 3 …”

Section: Inherent Totheproposeduseofcontinuousmentioning

confidence: 99%

QTc Interval Prolongation and Severe Apneas Associated With a Change in Infant Positioning

et al. 2013

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For more than a decade there has been considerable interest in the role of QT interval prolongation in the pathogenesis of sudden infant death syndrome. It has been proposed that the QT interval is a surrogate marker for autonomic instability and can be used to identify infants at risk for significant morbidity and mortality, including sudden infant death syndrome. We present the case of an infant that experienced a significant increase in his QTc, as detected by continuous QTc monitoring in the NICU after repositioning from a supine to prone position. This increase from a 413 ± 6 millisecond baseline average to 500 milliseconds was sustained for 2 hours and associated with clinically relevant apnea that ultimately required repositioning of the infant back to the supine position. Repositioning resulted in an immediate decrease of the QTc back to the previous baseline and termination of the apneic events. This case demonstrates an example of how the use of continuous QTc monitoring in the NICU setting may be used to detect QTc-accentuating factors in real time and identify situations that cause perturbations in an infant’s autonomic nervous system.

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Philips QT Interval Measurement Algorithms for Diagnostic, Ambulatory, and Patient Monitoring ECG Applications

Abstract: The three variations of the QT measurement algorithm we developed are suitable for diagnostic 12-lead, Holter, and patient monitoring applications.

Cited by 48 publications

References 11 publications

Update to Practice Standards for Electrocardiographic Monitoring in Hospital Settings: A Scientific Statement From the American Heart Association

Update to Practice Standards for Electrocardiographic Monitoring in Hospital Settings: A Scientific Statement From the American Heart Association

Comparison of two automated methods for QT interval measurement

QTc Interval Prolongation and Severe Apneas Associated With a Change in Infant Positioning

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