Are Premature Birth and Low Birth Weight Associated with Delay on the Eruption of Deciduous Teeth? A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Objective: To investigate whether children with premature birth (PB) and/or with low birth weight (LBW) have different tooth eruption patterns than those born at term or with normal weight. Material and Methods: Searches were performed in the PubMed, Cochrane Library, Sc1opus, Web of Science, LILACS, and BBO databases as well as the grey literature. Three independent reviewers were involved in study selection, data extraction, and bias assessment. The risk of bias was assessed using the Modified Newcastle-Ottawa Scale. Meta-analysis was conducted to compute the mean difference (MD) in mean chronological or adjusted age at the eruption of the first deciduous tooth between preterm children and those born at full term. The GRADE approach was used. Results: Among a total of 316 articles identified, 21 were eligible for inclusion and three were included in the meta-analysis. PB was associated with the delay in the first tooth deciduous eruption when chronological age was considered (MD: 1.36; 95%CI: 1.02–1.69) but not when considering adjusted age (MD: -0.30; 95%CI: -0.67–0.07). The evidence was graded as having very low quality. Conclusion: Based on a low certainty of evidence the PB is associated with the delayed eruption of the first deciduous tooth when considering chronological age but not when adjusted age is considered.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".