A Sex- and Gender-Based Analysis of Adverse Drug Reactions: A Scoping Review of Pharmacovigilance Databases
Why this work is in the frame
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Bibliographic record
Abstract
Drug-related adverse events or adverse drug reactions (ADRs) are currently partially or substantially under-reported. ADR reporting systems need to expand their focus to include sex- and gender-related factors in order to understand, prevent, or reduce the occurrence of ADRs in all people, particularly women. This scoping review describes adverse drug reactions reported to international pharmacovigilance databases. It identifies the drug classes most commonly associated with ADRs and synthesizes the evidence on ADRs utilizing a sex- and gender-based analysis plus (SGBA+) to assess the differential outcomes reported in the individual studies. We developed a systematic search strategy and applied it to six electronic databases, ultimately including 35 papers. Overall, the evidence shows that women are involved in more ADR reports than men across different countries, although in some cases, men experience more serious ADRs. Most studies were conducted in higher-income countries; the terms adverse drug reactions and adverse drug events are used interchangeably, and there is a lack of standardization between systems. Additional research is needed to identify the relationships between sex- and gender-related factors in the occurrence and reporting of ADRs to adequately detect and prevent ADRs, as well as to tailor and prepare effective reporting for the lifecycle management of drugs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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 it