Dataset Information

Drug use and torsades de pointes cardiac arrhythmias in Sweden: a nationwide register-based cohort study.

ABSTRACT: OBJECTIVE:To study the occurrence of torsades de pointes (TdP) ventricular tachycardia in relation to use of drugs labelled with TdP risk, using two nationwide Swedish registers. DESIGN:Prospective register-based cohort study. SETTING:Entire Sweden. PARTICIPANTS:Persons aged ?18 years prescribed and dispensed any drug classified with TdP risk during 2006-2017, according to CredibleMeds. Persons with a registered TdP diagnosis during the study period, using drugs labelled with known (TdP 1), possible (TdP 2) or conditional (TdP 3) risk at the incident of TdP were examined. PRIMARY OUTCOME MEASURES:Occurrence of TdP in relation to exposure rates for individual drugs with TdP risk. SECONDARY OUTCOME MEASURES:Concurrent use of more than one TdP-labelled drug in a person with a TdP diagnosis. RESULTS:During the study period, 410 TdP cases using drugs with TdP risk labels at the incident were registered; 205 women and 205 men, mean age 74.0 and 71.5 years, respectively. Antidepressants dominated (129/410, 30%), followed by antiarrhythmics (17%). Diuretics and gastric acid-secretion inhibitors, with TdP risk related to induction of hypokalaemia or hypomagnesaemia, were used in 56% and 32% of the 410 TdP cases, respectively. Among the most used antidepressants, citalopram with known TdP 1 risk was associated with both a higher absolute number and incidence of TdP per 100?000 users (two to four times), compared with mirtazapine with possible (TdP 2), and sertraline with conditional (TdP 3) risk. Multiple risk factors, including advanced age, cardiovascular disease and treatment with more than one TdP-classified drug, were frequently observed. CONCLUSIONS:Antidepressants followed by antiarrhythmics dominated among TdP risk drugs used by adults with TdP diagnosis, the majority being ?65 years. TdP risk class and concomitant medication should be considered when prescribing antidepressants to older patients.

SUBMITTER: Danielsson B

PROVIDER: S-EPMC7069257 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Drug use and torsades de pointes cardiac arrhythmias in Sweden: a nationwide register-based cohort study.

Danielsson Bengt B Collin Julius J Nyman Anastasia A Bergendal Annica A Borg Natalia N State Maria M Bergfeldt Lennart L Fastbom Johan J

BMJ open 20200312 3

<h4>Objective</h4>To study the occurrence of torsades de pointes (TdP) ventricular tachycardia in relation to use of drugs labelled with TdP risk, using two nationwide Swedish registers.<h4>Design</h4>Prospective register-based cohort study.<h4>Setting</h4>Entire Sweden.<h4>Participants</h4>Persons aged ≥18 years prescribed and dispensed any drug classified with TdP risk during 2006-2017, according to CredibleMeds. Persons with a registered TdP diagnosis during the study period, using drugs labe ...[more]

PMID: 32169926

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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 use and torsades de pointes cardiac arrhythmias in Sweden: a nationwide register-based cohort study.

Publications

Drug use and torsades de pointes cardiac arrhythmias in Sweden: a nationwide register-based cohort study.

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