Torsade de Pointes/QT Prolongation Associated with Antifungal Triazoles: A Pharmacovigilance Study Based on the U.S. FDA Adverse Event Reporting System（FAERS）
Bibliographic record
Abstract
PURPOSE: Torsade de pointes (TdP)/QT prolongation is a fatal adverse event (AE) when using antifungal triazoles. We aimed to compare the AE signals of TdP/QT prolongation and onset time among different drugs of this kind comprehensively. METHODS: This retrospective research was to analyze the U.S. FDA Adverse Event Reporting System (FAERS) database containing 71 quarters of reports through online retrieval. We calculated the strength of signals of TdP/QT prolongation related to 4 drugs of triazoles by using the following indicators: reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC), and empirical Bayesian geometric mean (EBGM). The onset time to the AE of TdP/QT prolongation among different antifungal triazoles were compared by using nonparametric tests. Management and visualization of the data were performed by employing MySQL Workbench and R software. The data information including clinical features, AE onset time, and outcomes were extracted for analysis as well. RESULTS: After filtering the FAERS database, 448 reports were identified that were associated with TdP/QT prolongation when 4 triazoles played the primary suspected role. The AE signals of TdP/QT prolongation for any involved antifungal triazoles were detected by using the 4 detection indicators, and the signals of fluconazole are the strongest. This AE mostly occurred within 0-14 days after triazoles therapy. CONCLUSIONS: The AE signals of TdP/QT prolongation associated with antifungal triazoles were very intense. Attention must be paid to the TdP/QT prolongation of various triazoles, particularly at the early stages of antifungal triazoles treatment.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".