Quetiapine, QTc interval prolongation, and <i>torsade de pointes</i> : a review of case reports
Bibliographic record
Abstract
Recently, both the manufacturer of quetiapine and the US Food and Drug Administration warned healthcare providers and patients about quetiapine-induced QTc interval prolongation and torsade de pointes (TdP) when using this drug within the approved labeling. We reviewed the case-report literature and found 12 case reports of QTc interval prolongation in the setting of quetiapine administration. There were no cases of quetiapine-induced TdP or sudden cardiac death (SCD) among patients using quetiapine appropriately and free of additional risk factors for QTc interval prolongation and TdP. Among the 12 case reports risk factors included female sex (nine cases), coadministration of a drug associated with QTc interval prolongation (eight cases), hypokalemia or hypomagnesemia (six cases) quetiapine overdose (five cases), cardiac problems (four cases), and coadministration of cytochrome P450 3A4 inhibitors (two cases). There were four cases of TdP. As drug-induced TdP is a rare event, prospective studies to evaluate the risk factors associated with QTc prolongation and TdP are difficult to design, would be very costly, and would require very large samples to capture TdP rather than its surrogate markers. Furthermore, conventional statistical methods may not apply to studies of TdP, which is rare and an 'outlier' manifestation of QTc prolongation. We urge drug manufacturers and regulatory agencies to periodically publish full case reports of psychotropic drug-induced QTc interval prolongation, TdP, and SCD so that clinicians and investigators may better understand the clinical implications of prescribing such drugs as quetiapine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".