Estimates of population‐based incidence of malignant arrhythmias associated with medication use—a narrative review
Bibliographic record
Abstract
Certain medications are reported to be associated with acquired long-QT syndrome (ALQTS), which can degenerate into a potentially severe 'malignant' arrhythmia known as torsades de pointes (TdP). However, population-based estimations of the incidence of medication-associated malignant arrhythmia are limited. The purpose of this article is to review the clinical symptoms, cellular mechanism, categorization, and risk factors of these malignant arrhythmias, as well as illustrate results and methodological limitations of epidemiological literature which have previously estimated population-based incidence of ALQTS and malignant arrhythmia. Administrative databases in universal healthcare systems (such as Canada) can be used to provide a robust estimate of this incidence. We present a valid operational definition of medication-associated malignant arrhythmia, using Canadian hospital administrative data linked to prescription databases that can be used to estimate the population-based incidence. An estimation of incidence may have important implications with regard to understanding the potential widespread distribution of this adverse effect-which may influence medication prescribing patterns.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".