Contribution of Latin America to Pharmacovigilance
Bibliographic record
Abstract
BACKGROUND: Pharmacovigilance activities have been ongoing for 4 decades. However, little is known (especially outside of the area) about the contribution of Latin America to this field. OBJECTIVE: To review and quantify the published literature on pharmacovigilance in Latin American countries. DATA SOURCES: We searched electronic databases including MEDLINE (1966-2004), EMBASE (1980-2004), International Pharmaceutical Abstracts (1970-2004), Toxline (1992-2004), Literatura Latino-Americana e do Caribe em Ciências da Saúde (1982-2004), Sistema de Información Esencial en Terapéutica y Salud (1980-2004), and the Pan American Health Organization Web site (1970-2004) for articles on pharmacovigilance or adverse drug reactions in any of the 19 major Latin American countries. Papers were retrieved and categorized according to content and country of origin by 2 independent reviewers. STUDY SELECTION AND DATA EXTRACTION: There were 195 usable articles from 13 countries. DATA SYNTHESIS: Fifty-one of the papers retrieved dealt with pharmacovigilance centers (15 national centers, 10 hospitals, 26 other), 55 covered pharmacovigilance itself (21 theoretical papers, 9 with description of models, 25 educational papers), and 89 were pharmacoepidemiologic studies of adverse drug reactions (69 case reports, 13 observational cohorts, 2 cohort studies, 1 randomized clinical trial, 4 clinical papers on adverse reaction management). Studies have increased exponentially since 1980. Five countries (Argentina, Brazil, Chile, Costa Rica, Venezuela) published reports from national centers. No studies were found from 6 countries: Dominican Republic, El Salvador, Honduras, Nicaragua, Paraguay, or Uruguay. Most studied categories were antiinfectives and drugs affecting the central nervous system, cardiovascular system, and musculoskeletal system. CONCLUSIONS: Contributions of Latin American countries to the field of pharmacovigilence have been remarkable, considering the constraints on these countries. A need exists for an increased number of formal pharmacovigilance studies and research using methodologically stronger pharmacoepidemiologic models.
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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 | 0.021 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".