Bibliographic record
Abstract
Torsades de pointes (TdP) is a life-threatening arrhythmia associated with prolongation of the corrected QT (QTc) interval on the electrocardiogram. More than 100 drugs available in Canada, including widely used antibiotics, antidepressants, cardiovascular drugs and many others, may cause QTc interval prolongation and TdP. Risk factors for TdP include QTc interval >500 ms, increase in QTc interval ≥60 ms from the pretreatment value, advanced age, female sex, acute myocardial infarction, heart failure with reduced ejection fraction, hypokalemia, hypomagnesemia, hypocalcemia, bradycardia, treatment with diuretics and elevated plasma concentrations of QTc interval-prolonging drugs due to drug interactions, inadequate dose adjustment of renally eliminated drugs in patients with kidney disease and rapid intravenous administration. Pharmacokinetic drug interactions associated with the highest risk of TdP include antifungal agents, macrolide antibiotics (except azithromycin) and drugs to treat human immunodeficiency virus interacting with amiodarone, disopyramide, dofetilide or pimozide. Other important pharmacokinetic interactions include antidepressants (bupropion, duloxetine, fluoxetine, paroxetine) interacting with flecainide, quinidine or thioridazine. Pharmacists play an important role in minimizing the risk of drug-induced QTc interval prolongation and TdP through knowledge of drugs that are associated with a known or possible risk of TdP, individualized assessment of risk of drug-induced QTc interval prolongation, awareness of drug interactions most likely to result in TdP and attention to dose reduction of renally eliminated QTc interval-prolonging drugs in patients with kidney disease. Treatment of hemodynamically stable TdP consists of discontinuation of the offending drug(s), correction of electrolyte abnormalities and administration of intravenous magnesium sulfate 1 to 2 g.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".