Exposição ocupacional a agrotóxicos organofosforados e neoplasias hematológicas: uma revisão sistemática
Bibliographic record
Abstract
OBJECTIVE: To update findings of observational analytical studies on the association between occupational exposure to organophosphates and hematologic malignancies. METHODOLOGY: Systematic literature review, including cohort and case-control studies, without limitation of publication time, in Portuguese and English. The articles were traced from June 2017 to July 2019 in PubMed, MEDLINE, LILACS, Web of Science, and Scopus databases. The qualitative bias risk assessment was performed using the Newcastle-Ottawa Scale and the Downs and Black Checklist. Results were presented according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). RESULTS: Seventeen studies evaluated as good/high methodological quality were eligible. Exposure to diazinon (1 cohort), phonophos (1 cohort), dichlorvos, crotoxiphos and famphur (1 case control) was associated with leukemia, while exposure to organophosphate was associated to lymphomas (6 case control); the risk of non-Hodgkin's lymphoma was higher in those exposed to diazinon (1 control case) and malathion (3 control case) than non-exposed ones. Multiple myeloma occurred more commonly in organophosphate exposed than in non-exposed individuals (1 case-control). CONCLUSION: Occupational exposure to organophosphates increases the risk of hematologic malignancies, especially among individuals with longer exposure periods. Worker monitoring and exposure control measures are recommended.
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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 | 0.020 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".