Paraquat and Parkinson’s disease: a systematic review protocol according to the OHAT approach for hazard identification
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative condition that has genetic susceptibility, aging, and exposure to certain chemicals as risk factors. In recent decades, epidemiological and experimental studies have investigated the role of pesticides in the development of PD, in particular that of the herbicide paraquat. Here, we, therefore, aim to systematically review the association between paraquat exposure and PD. METHODS: Observational studies (cohort, case-control, and cross-sectional) eligible for this systematic review will enroll any participant who was occupationally and/or environmentally exposed to paraquat. Experimental studies, including in vivo and in vitro assays designed to assess neurotoxicological endpoints or mechanisms of paraquat neurotoxicity, will also be eligible. Outcomes of interest include the following: PD diagnosis; neurobehavioral, biochemical, and/or morphological alterations; and cellular, biochemical, and/or molecular pathways to oxidative stress. Using terms to include all forms of paraquat combined with PD, the following electronic databases will be searched: PubMed, EMBASE, LILACS, Toxnet, and Web of Science, without restrictions as to language, year, or status of publication. A team of reviewers will independently select potential titles and abstracts, extract data, assess risk of bias, and determine the overall quality of evidence for each outcome using the Office of Health Assessment and Translation (OHAT) approach for systematic reviews and evidence integration. Dichotomous data will be summarized as odds ratios, and continuous data will be given as mean differences, both with their respective 95% confidence intervals. DISCUSSION: This is the first time that the OHAT systematic review protocol will be applied to investigate a possible causal association between exposure to paraquat and PD. Results from this study could serve as basis for regulatory agencies to define paraquat levels of concern, supporting its risk assessment process. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016050861.
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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 | 0.074 | 0.080 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.020 | 0.018 |
| Bibliometrics | 0.018 | 0.014 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.050 | 0.007 |
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".