Fluoroquinolones and the Risk of Serious Arrhythmia: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Fluoroquinolones have been suspected to cause cardiac arrhythmia but data are lacking, particularly for the individual fluoroquinolones. We assessed the risk of serious arrhythmia, defined as ventricular arrhythmia or sudden/unattended death identified in hospital discharge diagnoses, related to fluoroquinolones as a class as well as for each individual molecule. METHODS: We used a cohort of patients treated for respiratory conditions from 1 January 1990 to 31 December 2005, identified using the healthcare databases from the province of Quebec (Canada), with follow-up until 31 March 2007. A nested case-control analysis was performed within this cohort, with all cases of serious arrhythmia occurring during follow-up identified from hospitalization records. These cases were matched with up to 20 controls. Conditional logistic regression was used to compute adjusted rate ratios (RRs) of serious arrhythmia associated with fluoroquinolone use. RESULTS: Within the cohort of 605127 subjects, 1838 cases were identified (incidence rate=4.7/10000 person-years). The rate of serious arrhythmia was elevated with current fluoroquinolone use (RR=1.76; 95% confidence interval [CI], 1.19-2.59), in particular with new current use (RR=2.23; 95% CI, 1.31-3.80). Gatifloxacin use was associated with the highest rate (RR=7.38; 95% CI, 2.30-23.70); moxifloxacin and ciprofloxacin were also associated with elevated rates of serious arrhythmia (RR=3.30; 95% CI, 1.47-7.37 and RR=2.15; 95% CI, 1.34-3.46, respectively). CONCLUSIONS: The use fluoroquinolones is associated with an elevated risk of serious arrhythmia, with some differences among molecules. Given that the individual fluoroquinolones share various indications, the relative risks of serious arrhythmia could inform the choice of different molecules in high-risk patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".