Azithromycin, cardiovascular risks, QTc interval prolongation, <i>torsade de pointes</i> , and regulatory issues: A narrative review based on the study of case reports
Bibliographic record
Abstract
Over the past year, three articles have appeared in the New England Journal of Medicine describing conflicting findings about azithromycin and cardiac safety, particular azithromycin-induced QTc interval prolongation and torsade de pointes. The FDA wants healthcare providers to consider azithromycin-induced fatal cardiac arrhythmias for patients already at risk for cardiac death and other potentially arrhythmogenic cardiovascular conditions. In a systematic review of case reports we sought to determine factors that link to azithromycin-induced/associated QTc interval prolongation and torsade de pointes. We found 12 cases: seven female and five male. Of the nine adults with reported azithromycin doses, concurrent QTc interval measurement, and without congenital long QT syndrome, we found no significant relationship between dose and QTc interval duration. Additional risk factors were female sex, older age, heart disease, QTc interval prolonging drugs and metabolic inhibitors, hypokalemia, and bradycardia. All 12 subjects had at least two additional risk factors. Elderly women with heart disease appear to be at particularly risk for drug-related QTc interval prolongation and torsade de pointes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| 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) | 0.002 | 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".