A systematic review and meta‐analysis of systemic exposure associated with molar incisor hypomineralization
Bibliographic record
Abstract
OBJECTIVE: To evaluate systemic exposures associated with molar incisor hypomineralization (MIH). METHODS: This systematic review was performed using published observational studies that evaluated the systemic exposures associated with MIH. The sources of articles searched were PubMed, Scopus, Web of Science, LILACS, BBO, Cochrane Library and Grey literature. The risk of bias was analysed according to the Newcastle-Ottawa Scale for quality assessment. The meta-analysis was performed considering the exposures during the prenatal, perinatal and postnatal periods using the CMA software. RESULTS: A total of 4207 articles were identified. Twenty-nine studies were eligible for inclusion and 27 were included in the meta-analysis. The studies presented low and moderate risks of bias, except for one that was classified as having a high risk of bias. Maternal illness during pregnancy (OR 1.40; 95% CI 1.18-1.65, P < 0.0001) and psychological stress (OR = 2.65; 95% CI 1.52-4.63; P = 0.001) was observed to be significantly associated with higher odds of MIH. During the perinatal period, caesarean delivery (OR = 1.32, 95% CI 1.11-1.57, P = 0.001) and delivery complications (OR = 2.06; 95% CI 1.47-2.88, P < 0.0001) were also associated with MIH. In the postnatal period, only respiratory diseases (OR = 1.98; 95% CI 1.45-2.70, P < 0.0001) and fever (OR = 1.50; 95% CI 1.22-1.84; P < 0.0001) were associated with higher prevalence of MIH. The evidence was graded as very low quality. CONCLUSIONS: Maternal illness, psychological stress, caesarean delivery, delivery complications, respiratory diseases and fever during the first years of a child's life were significantly associated with a higher odds of MIH. However, this should be interpreted with caution, once the primary studies were observational, with serious limitations according to the risk of bias, imprecision, and inconsistency. Further, well-designed cohort studies are still 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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".