首页> 外文期刊>Clinical Pharmacology and Therapeutics >A new paradigm for predicting risk of Torsades de Pointes during drug development: Commentary on: 'Improved prediction of drug-induced Torsades de Pointes through simulations of dynamics and machine learning algorithms'
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A new paradigm for predicting risk of Torsades de Pointes during drug development: Commentary on: 'Improved prediction of drug-induced Torsades de Pointes through simulations of dynamics and machine learning algorithms'

机译:预测药物开发过程中Torsades de Pointes风险的新范例:评论:“通过动力学模拟和机器学习算法改进了对药物诱发的Torsades de Pointes的预测”

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摘要

Drug-induced long QT syndrome (diLQTS) is a clinical entity in which administration of a drug produces marked prolongation of the QT interval on the ECG. DiLQTS places a patient at risk of developing Torsades de Pointes (TdP), a malignant polymorphic ventricular tachycardia associated with arrhythmic sudden cardiac death (SCD). In addition to diLQTS, other clinical risk factors for TdP include female gender, bradycardia, electrolyte disturbances, recent conversion to normal (sinus) rhythm, and congenital LQTS.
机译:药物诱发的长QT综合征(diLQTS)是一种临床实体,在这种临床实体中,药物的给药会使ECG上的QT间隔显着延长。 DiLQTS使患者有患扭转性心律失常性心脏死亡(SCD)的恶性多形性室性心动过速的风险,即发展为Torsades de Pointes(TdP)。除diLQTS外,TdP的其他临床危险因素还包括女性,心动过缓,电解质紊乱,近期转为正常(窦性)节律和先天性LQTS。

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