Mechanisms of torsade de pointes tachycardia in patients with spontaneous high-degree atrioventricular block: A modern look at old data

Fontaine, G.; Li, Guoliang; Saguner, Ardan M.; Frank, Robert

doi:10.1016/j.jelectrocard.2019.05.007

Cited by 5 publications

(2 citation statements)

References 23 publications

(27 reference statements)

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“…Moreover, ventricular arrhythmias in rat hearts tend to self‐terminate 11 . Owing to the small ventricular mass of the rat heart, it is not possible to maintain the re‐entrant circuits which give rise to TdP, 40 because re‐entry depends on tissue size 10 . Because of the lack of effect of torsadogenic drugs on the heart rhythm, rodents are even not recommended for non‐clinical assessment of the effect of pharmaceuticals on ventricular repolarization and proarrhythmic risk in vivo, unlike larger species, such as dog, monkey, swine, rabbit, ferret, and guinea pig 39 .…”

Section: Discussionmentioning

confidence: 99%

Rapid changes of mRNA expressions of cardiac ion channels affected by Torsadogenic drugs influence susceptibility of rat hearts to arrhythmias induced by Beta‐Adrenergic stimulation

Hadova,

Kmecova,

Ochodnicka‐Mackovicova

et al. 2023

Pharmacology Res & Perspec

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Drug‐induced long QT syndrome (LQTS) and Torsades de Pointes (TdP) are serious concerns in drug development. Although rats are a useful scientific tool, their hearts, unlike larger species, usually do not respond to torsadogenic drugs. Consequently, their resistance to drug‐induced arrhythmias is poorly understood. Here, we challenged rats with rapid delayed rectifier current (Ikr)‐inhibiting antibiotic clarithromycin (CLA), loop diuretic furosemide (FUR) or their combination (CLA + FUR), and examined functional and molecular abnormalities after stimulation with isoproterenol. Clarithromycin and furosemide were administered orally at 12‐h intervals for 7 days. To evaluate electrical instability, electrocardiography (ECG) was recorded either in vivo or ex vivo using the Langendorff‐perfused heart method under basal conditions and subsequently under beta‐adrenergic stimulation. Gene expression was measured using real‐time quantitative PCR in left ventricular tissue. Indeed, FUR and CLA + FUR rats exhibited hypokalemia. CLA and CLA + FUR treatment resulted in drug‐induced LQTS and even an episode of TdP in one CLA + FUR rat. The combined treatment dysregulated gene expression of several ion channels subunits, including KCNQ1, calcium channels and Na+/K + ‐ATPase subunits, while both monotherapies had no impact. The rat with recorded TdP exhibited differences in the expression of ion channel genes compared to the rest of rats within the CLA + FUR group. The ECG changes were not detected in isolated perfused hearts. Hence, we report rapid orchestration of ion channel reprogramming of hearts with QT prolongation induced by simultaneous administration of clarithromycin and furosemide in rats, which may account for their ability to avoid arrhythmias triggered by beta‐adrenergic stimulation.

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Section: Discussionmentioning

confidence: 99%

Rapid changes of mRNA expressions of cardiac ion channels affected by Torsadogenic drugs influence susceptibility of rat hearts to arrhythmias induced by Beta‐Adrenergic stimulation

Hadova,

Kmecova,

Ochodnicka‐Mackovicova

et al. 2023

Pharmacology Res & Perspec

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“…In [18] a new classifier model based on kernel driven classifier is presented. The authors in [19,20] outlines the application of artificial neural network (ANN) and SVM model in classification. Similarly, a cross wavelet transform (XWT) is outlined in [21], where two distinct signals are correlated in deriving the correlation.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Classification Approach using Feature Fusion Model for Heart Disease Diagnosis

Vasantrao¹,

Rangasamy²,

Shelke³

2022

IJACSA

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Early Diagnosis has a very critical role in medical data processing and automated system. In medical diagnosis, automation is focused in different area of applications, in which heart disease diagnosis is a prominent domain. An early detection of heart disease can save many lives or criticality issues in diagnosing patients. In the process of heart disease diagnosis spatial and frequency domain features are used in making decision by the automation system. The processing features are observed to time variant or invariant in nature and the criticality of the observing feature varies with the diagnosis need. Wherein, the current automation system utilizes the features extracted in a large count to attain a higher accuracy, the processing overhead, and delay are considerable. Different regression approaches were developed in recent past to minimize the processing feature overhead the features are optimized based on gain performance or distance factors. The characteristic variation of feature and the significance of the feature vector are not addressed. This paper outlines a method of feature selection for heart disease diagnosis, based on weighted method of feature vector in consideration of feature significance and probability of estimate. A new optimizing function for feature selection is proposed as a dual function of probability factor and feature weight value. Simulation results illustrate the improvement of accuracy and speed of computation using proposed method compared to other existing methods.

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Traditional risk factors for QT interval prolongation and torsades de pointes

Sowinski

Kovacs

Tisdale

2022

Torsades De Pointes

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Mechanisms of torsade de pointes tachycardia in patients with spontaneous high-degree atrioventricular block: A modern look at old data

Cited by 5 publications

References 23 publications

Rapid changes of mRNA expressions of cardiac ion channels affected by Torsadogenic drugs influence susceptibility of rat hearts to arrhythmias induced by Beta‐Adrenergic stimulation

Rapid changes of mRNA expressions of cardiac ion channels affected by Torsadogenic drugs influence susceptibility of rat hearts to arrhythmias induced by Beta‐Adrenergic stimulation

A Deep Learning Classification Approach using Feature Fusion Model for Heart Disease Diagnosis

Traditional risk factors for QT interval prolongation and torsades de pointes

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