Dataset Information

Drug-induced 'Torsade de Pointes' in a COVID-19 patient despite discontinuation of chloroquine. Importance of its long half-life: a case report.

ABSTRACT:

Background

Early studies have led to the repositioning of a subgroup of antimalarial agents (e.g. chloroquine and hydroxychloroquine) as antiviral treatment in coronavirus disease 2019 (COVID-19) patients. These drugs are now being prescribed based on small non-controlled studies, but larger controlled studies have yet to demonstrate the positive effect of these drugs. In addition, these drugs are also known for their QT interval-prolonging effect associated with significant morbidity and mortality.

Case summary

We present a case of a 66-year-old female admitted to the intensive care unit with respiratory failure due to COVID-19. She was treated with chloroquine (QTc interval at baseline was 429 ms). Despite cessation of chloroquine, but after the start of erythromycin, she developed severe QTc interval prolongation (QTc interval 550 ms) and 'Torsade de Pointes'. Two weeks after cessation of all QTc interval-prolonging drugs, the QTc interval was restored.

Discussion

The elimination half-life of chloroquine ranges from days up to weeks. Even after discontinuation of chloroquine, ECG monitoring in COVID-19 patients is warranted. We recommend observation of the QT interval after cessation of chloroquine in cases where other potentially QT interval-prolonging drugs are introduced.

SUBMITTER: Semedo E

PROVIDER: S-EPMC7454487 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Drug-induced 'Torsade de Pointes' in a COVID-19 patient despite discontinuation of chloroquine. Importance of its long half-life: a case report.

Semedo Edimir E Kapel Gijs F GF van Opstal Jurren J van Dessel Pascal F H M PFHM

European heart journal. Case reports 20200721 FI1

<h4>Background</h4>Early studies have led to the repositioning of a subgroup of antimalarial agents (e.g. chloroquine and hydroxychloroquine) as antiviral treatment in coronavirus disease 2019 (COVID-19) patients. These drugs are now being prescribed based on small non-controlled studies, but larger controlled studies have yet to demonstrate the positive effect of these drugs. In addition, these drugs are also known for their QT interval-prolonging effect associated with significant morbidity an ...[more]

PMID: 33089050

Similar Datasets

Project description:BACKGROUND:Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP). Therefore recognizing drugs with TdP risk is essential. Candidate drugs that are determined not to cause cardiac ion channel blockage are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects. The objective of the present study is to develop an SAR (Structure-Activity Relationship) model that can be used as an early screen for torsadogenic (causing TdP arrhythmias) potential in drug candidates. The method is performed using descriptors comprised of atomic NMR chemical shifts (13C and 15N NMR) and corresponding interatomic distances which are combined into a 3D abstract space matrix. The method is called 3D-SDAR (3-dimensional spectral data-activity relationship) and can be interrogated to identify molecular features responsible for the activity, which can in turn yield simplified hERG toxicophores. A dataset of 55 hERG potassium channel inhibitors collected from Kramer et al. consisting of 32 drugs with TdP risk and 23 with no TdP risk was used for training the 3D-SDAR model. RESULTS:An artificial neural network (ANN) with multilayer perceptron was used to define collinearities among the independent 3D-SDAR features. A composite model from 200 random iterations with 25% of the molecules in each case yielded the following figures of merit: training, 99.2%; internal test sets, 66.7%; external (blind validation) test set, 68.4%. In the external test set, 70.3% of positive TdP drugs were correctly predicted. Moreover, toxicophores were generated from TdP drugs. CONCLUSION:A 3D-SDAR was successfully used to build a predictive model for drug-induced torsadogenic and non-torsadogenic drugs based on 55 compounds. The model was tested in 38 external drugs.

Dataset Information

Drug-induced 'Torsade de Pointes' in a COVID-19 patient despite discontinuation of chloroquine. Importance of its long half-life: a case report.

Background

Case summary

Discussion

Publications

Drug-induced 'Torsade de Pointes' in a COVID-19 patient despite discontinuation of chloroquine. Importance of its long half-life: a case report.

Similar Datasets

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