Comparison of Two Methods of Estimating Reader Variability in QT Interval Measurements in Thorough QT/QTc Studies

Salvi, Vaibhav; Karnad, Dilip R.; Kerkar, Vaibhav; Panicker, Gopi Krishna; Natekar, Mili; Kothari, Snehal

doi:10.1111/anec.12136

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…7(a) and (b) was 2.75 ± 2.21 ms. This mean was smaller than the average of the differences among readers of cardiologists that was 5.4 ms [24]. In the right side of Fig.…”

Section: Resultsmentioning

confidence: 74%

Proposal of a pseudo‐electrocardiogram model incorporating heart rate variability and QT‐interval variability, and its application

Ueyama

Yoshino

Nakamura

et al. 2022

IEEJ Transactions Elec Engng

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In this work, we propose a model that incorporates QT‐interval variability (QTV) by extending the synthetic electrocardiogram (ECG) model including heart rate variability (HRV). The model consists of three modified coupled ordinary differential equations and an equation to incorporate QTV by shifting the position of the T‐wave; in addition, RR and QT tachograms that have frequency characteristics composed of multiple Gaussian distribution peaks are used. An ECG signal can be generated by adapting a certain ECG waveform and by giving the means, standard deviations, and power spectral density parameters of HRV and QTV. This proposed model may reveal the neurophysiological mechanisms underlying the relationship between QTV and HRV and/or the autonomic activity, and it may solve problems in the measurement of QT‐interval. In conclusion, this proposed model is a very useful tool in medical education and experimental simulation. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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“…7(a) and (b) was 2.75 ± 2.21 ms. This mean was smaller than the average of the differences among readers of cardiologists that was 5.4 ms [24]. In the right side of Fig.…”

Section: Resultsmentioning

confidence: 74%

Proposal of a pseudo‐electrocardiogram model incorporating heart rate variability and QT‐interval variability, and its application

Ueyama

Yoshino

Nakamura

et al. 2022

IEEJ Transactions Elec Engng

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“…To obtain a SW-ECG, patients were instructed to hold the stainless steel ring on the top case of the SW continuously for 30 s. Readings from the automated SW-algorithm (HR, PR-, and QT-interval plus QTc) were recorded and a PDF-file of the 30 s single-lead (lead I) SW-ECG was saved. QT-interval on the corresponding 12-lead ECG was manually interpreted by two blinded, independent cardiologists applying the tangent-method ( 8 ), using lead II or V5/V6 as suggested in previous work ( 6 , 8 , 9 ). Bazett’s formula was used to calculate QTc ( 10 ).…”

Section: Methodsmentioning

confidence: 99%

Clinical Validation of Automated Corrected QT-Interval Measurements From a Single Lead Electrocardiogram Using a Novel Smartwatch

Mannhart

Hennings

Lischer

et al. 2022

Front. Cardiovasc. Med.

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IntroductionThe Withings Scanwatch (Withings SA, Issy les Moulineaux, France) offers automated analysis of the QTc. We aimed to compare automated QTc-measurements using a single lead ECG of a novel smartwatch (Withings Scanwatch, SW-ECG) with manual-measured QTc from a nearly simultaneously recorded 12-lead ECG.MethodsWe enrolled consecutive patients referred to a tertiary hospital for cardiac workup in a prospective, observational study. The QT-interval of the 12-lead ECG was manually interpreted by two blinded, independent cardiologists through the tangent-method. Bazett’s formula was used to calculate QTc. Results were compared using the Bland-Altman method.ResultsA total of 317 patients (48% female, mean age 63 ± 17 years) were enrolled. HR-, QRS-, and QT-intervals were automatically calculated by the SW in 295 (93%), 249 (79%), and 177 patients (56%), respectively. Diagnostic accuracy of SW-ECG for detection of QTc-intervals ≥ 460 ms (women) and ≥ 440 ms (men) as quantified by the area under the curve was 0.91 and 0.89. The Bland-Altman analysis resulted in a bias of 6.6 ms [95% limit of agreement (LoA) –59 to 72 ms] comparing automated QTc-measurements (SW-ECG) with manual QTc-measurement (12-lead ECG). In 12 patients (6.9%) the difference between the two measurements was greater than the LoA.ConclusionIn this clinical validation of a direct-to-consumer smartwatch we found fair to good agreement between automated-SW-ECG QTc-measurements and manual 12-lead-QTc measurements. The SW-ECG was able to automatically calculate QTc-intervals in one half of all assessed patients. Our work shows, that the automated algorithm of the SW-ECG needs improvement to be useful in a clinical setting.

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“…A specific assessment of reader variability is also required, with a subset of the ECGs being reread to quantify inter‐ and intrareader variability. Each core lab should have a well‐defined approach to quantifying reader variability …”

Section: Technical Challenges In Conducting a Tqt Studymentioning

confidence: 99%

“…Each core lab should have a well-defined approach to quantifying reader variability. 32 Reviews published in 2005 by Strnadova 33 and 2011 by Satin and colleagues 34 capture respective "snapshots in time" in this field. References to examples of individual TQT studies and related considerations are provided.…”

Section: Technical Challenges In Conducting a Tqt Studymentioning

confidence: 99%

Drug‐induced Proarrhythmia and Torsade de Pointes: A Primer for Students and Practitioners of Medicine and Pharmacy

Turner

Rodríguez

Mantovani

et al. 2018

The Journal of Clinical Pharma

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Multiple marketing withdrawals due to proarrhythmic concerns occurred in the United States, Canada, and the United Kingdom in the late 1980s to early 2000s. This primer reviews the clinical implications of a drug's identified proarrhythmic liability, the issues associated with these safety-related withdrawals, and the actions taken by the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) and by regulatory agencies in terms of changing drug development practices and introducing new nonclinical and clinical tests to asses proarrhythmic liability. ICH Guidelines S7B and E14 were released in 2005. Since then, they have been adopted by many regional regulatory authorities and have guided nonclinical and clinical proarrhythmic cardiac safety assessments during drug development. While this regulatory paradigm has been successful in preventing drugs with unanticipated potential for inducing the rare but potentially fatal polymorphic ventricular arrhythmia torsade de pointes from entering the market, it has led to the termination of drug development programs for other potentially useful medicines because of isolated results from studies with limited predictive value. Research efforts are now exploring alternative approaches to better predict potential proarrhythmic liabilities. For example, in the domain of human electrocardiographic assessments, concentration-response modeling conducted during phase 1 clinical development has recently become an accepted alternate primary methodology to the ICH E14 "thorough QT/QTc" study for defining a drug's corrected QT interval prolongation liability under certain conditions. When a drug's therapeutic benefit is considered important at a public health level but there is also an identified proarrhythmic liability that may result from administration of the single drug in certain individuals and/or drug-drug interactions, marketing approval will be accompanied by appropriate directions in the drug's prescribing information. Health-care professionals in the fields of medicine and pharmacy need to consider the prescribing information in conjunction with individual patients' clinical characteristics and concomitant medications when prescribing and dispensing such drugs.

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Comparison of Two Methods of Estimating Reader Variability in QT Interval Measurements in Thorough QT/QTc Studies

Cited by 6 publications

References 13 publications

Proposal of a pseudo‐electrocardiogram model incorporating heart rate variability and QT‐interval variability, and its application

Proposal of a pseudo‐electrocardiogram model incorporating heart rate variability and QT‐interval variability, and its application

Clinical Validation of Automated Corrected QT-Interval Measurements From a Single Lead Electrocardiogram Using a Novel Smartwatch

Drug‐induced Proarrhythmia and Torsade de Pointes: A Primer for Students and Practitioners of Medicine and Pharmacy

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