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Record W6922406023 · doi:10.1192/j.eurpsy.2023.1129

Torsade de Pointes: are psychotropic drugs at the heart of the matter? A retrospective case-control study led at the Montreal Heart Institute

2023· article· en· W6922406023 on OpenAlexaffabout

Bibliographic record

VenuePubMed Central · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsPsychotropic drugAntipsychoticPsychotropic AgentAntidepressantPsychotropic medicationPsychoactive drugQT intervalRetrospective cohort studyDrug

Abstract

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INTRODUCTION: Psychotropic drugs are the first-line medications in the treatment of psychosis, bipolar, anxiety and depressive disorders. Some of these psychoactive agents are suspected to be linked to rare, but lethal, ventricular arrhythmias, known as Torsade de Pointes (TdP). Most of the studies found an association between these classes of psychiatric agents and a prolongation of the corrected QT interval. However, QTc prolongation remains an imperfect, though well-established marker of risk for TdP and little is known about the relation between psychotropic drugs and TdP. Some physicians hence refrain from prescribing psychotropic medications to their patients for fear of cardiac adverse events, which can severely undermine the management of underlying psychiatric conditions. It is thus crucial to evaluate the relation between psychotropic medication use and the occurrence of TdP. OBJECTIVES: The primary objective of this study is to assess the relative contribution of psychotropic medications (antidepressants, antipsychotics) among all TdP risk factors (e.g. sex, hypokalemia, antiarrhythmic drug use). We hypothesize that psychotropic drug use will indeed be associated to TdP, but that this association is negligeable compared to other TdP risk factors. METHODS: A retrospective case-control study (1 :3 ratio) of patients hospitalized at the Montreal Heart Institute was carried out (n=444). RESULTS: Antidepressant and antipsychotic medication use proportions among the cases are 27% and 12% respectively, compared to 17% and 5% in controls (p= .018407 and p= .016326). In our study, patients who take antidepressants [OR=1.83; 95% CI 1.10-3.04] or antipsychotics [OR=2.47; 95% CI 1.16-5.26] are more likely to experience TdP. Patients with a psychotropic polypharmacy are also more prone to TdP [OR=5.67; 95% CI 2.58-12.42]. However, cases are also significantly more likely (p=.000281) to take concomitant medications associated with QTc prolongation (based on CredibleMeds, July 2022 list). Female sex [OR=2.40; 95% CI 1.55-3.71], hypokalemia [OR=3.46; 95% CI 1.65-7.26], kidney failure [OR=1.61; 95% CI 1.05-2.48], a QTc interval greater or equal to 500 ms [OR=5.89; 95% CI 3.59-9.65] are also associated with TdP. CONCLUSIONS: In this study, psychotropic drug use is indeed associated to TdP. Further analyses, i.e. multivariate logistic regressions, will determine psychotropic drugs’ relative contribution among the identified risk factors for TdP. DISCLOSURE OF INTEREST: None Declared

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.206
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes2
Has abstractyes

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