Neuropsychiatric Adverse Reactions to Mefloquine: a Systematic Comparison of Prescribing and Patient Safety Guidance in the US, UK, Ireland, Australia, New Zealand, and Canada
Bibliographic record
Abstract
INTRODUCTION: The antimalarial drug mefloquine (MQ) is associated with neuropsychiatric adverse reactions, some of which may predict the development of more serious effects. Although prescribing guidance in the United States drug label (DL) recommends to discontinue MQ at the onset of neuropsychiatric symptoms, only certain reactions are listed in both the DL and the corresponding patient medication guide with a recommendation to discontinue or to consult a physician should they occur. To identify possible prodromal reactions for which there is complete or partial agreement in prescribing and patient recommendations, a systematic comparison of international drug safety labeling was performed. METHODS: The full text of each DL and medication guide (or equivalent) from six primarily English-speaking countries was reviewed to identify specific reactions with corresponding recommendations in drug safety labeling. Percentage agreement across the countries in corresponding recommendations was determined by MedDRA(®) high level group term (HLGT). RESULTS: Recommendations were found for reactions in 22 neuropsychiatric HLGTs. Complete or partial international agreement was found for reactions in 11 (50%) HLGTs. CONCLUSION: This analysis suggests opportunities for physicians to improve patient counseling and for international drug regulators to clarify language in MQ safety labeling to reflect national risk-benefit considerations.
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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 | 0.027 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".