The impact of environmental cadmium exposure on type 2 diabetes risk: a protocol for an overview of systematic reviews
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a worldwide epidemic, and while its etiology is polygenic, the role of environmental contaminant exposure in T2DM pathogenesis is of increasing importance. However, the evidence presented in systematic reviews on the relationship between cadmium exposure and T2DM development is inconsistent. This overview aims to assess existing evidence from systematic reviews linking cadmium exposure to T2DM and select metabolic disorders in humans. METHODS: Searches will be conducted in Medline, Embase, Web of Science, GEOBASE, BIOSIS Previews, and Cochrane Database of Systematic Reviews. Two reviewers (J.H and S.T.) will independently complete screening, data abstraction, risk of bias evaluation, and quality assessment. The primary outcome will be the association between cadmium exposure and T2DM prevalence. Secondary outcomes will include prediabetes, obesity, dyslipidemia, hypertension, and non-alcoholic fatty liver disease. We will perform a meta-analysis if two or more studies assess similar populations, utilize analogous methods, have related study designs, and evaluate similar outcomes. DISCUSSION: This overview will assess current evidence from systematic reviews for the association between cadmium exposure and risk of T2DM and other metabolic morbidities. This overview may be helpful for policy-makers and healthcare teams aiming to mitigate T2DM risk in populations at risk of cadmium exposure. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019125956.
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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 | 0.069 | 0.118 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.019 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.059 | 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".