Dental amalgams and risk of gestational hypertension in the MIREC study
Bibliographic record
Abstract
BACKGROUND: The potential association between the presence or replacement of dental amalgams and gestational hypertension (GH) is unclear. OBJECTIVE: To assess the association between the presence or replacement of dental amalgams and the risk of GH in a prospective cohort study. METHODS: We assessed dental amalgam status (presence or replacement), blood mercury concentrations, and measured blood pressure (BP) in 1817 pregnant women recruited in 10 Canadian cities. BP was assessed in each trimester of pregnancy and mercury concentrations in 1st and 3rd trimesters. Logistic regression analysis was performed to estimate the adjusted odds ratios (aOR) and 95% confidence intervals (CI) for the associations between dental amalgam status and GH. Concurrent measures with systolic BP (SBP) and diastolic BP (DBP) were assessing through linear generalized estimating equations. RESULTS: Dental amalgam status was weakly statistically correlated with mercury concentrations but there was no evidence of an association with GH in women having 1-4 (aOR = 1.31 (0.92, 1.85)) or ≥ 5 dental amalgams (aOR = 1.32 (0.86, 2.04)), compared to women without amalgam reported at first trimester. Dental amalgam replacement reported in the first or third trimester was similarly not associated with GH (aOR = 0.75 (0.40, 1.42) and 0.73 (0.39, 1.34), respectively) but with SBP (beta = -1.58 (-2.95, -0.02)). CONCLUSION: We found weak correlations between dental amalgams and blood mercury among pregnant women. However, the presence of dental amalgams or their replacement was not associated with GH but with decreased SBP for the replacement. Further studies are required.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".