Molar incisor hypomineralization and oral health-related quality of life in Brazilian children: A narrative review of current evidence
Bibliographic record
Abstract
The aim of this narrative review was to explore the association between Molar Incisor Hypomineralisation (MIH) and Oral Health-Related Quality-of-Life (OHRQoL) in Brazilian children aged 8-10 years. The study was developed considering the PRISMA guidelines (2020). Five databases were consulted to identify potential studies that used clinical parameters for the detection of MIH; and (b) studies that described aspects of the experience and severity of MIH; (c) records that adopted instruments recommended in the literature to explore OHRQoL in children, according to their respective age groups. The risk of bias of the included studies was analyzed using the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies. Of the 155 initially found, three were included. Of these, two were cross-sectional and one was a case-control study. The diagnosis of MIH was made according to the criteria of the European Academy of Paediatric Dentistry, and OHRQoL was identified using the Child Perceptions Questionnaire (CPQ8-10). The qualitative synthesis of the findings shows that no statistically significant association was identified between MIH and OHRQoL. Only the "oral symptoms domain" of the CPQ8-10 was associated with MIH. The studies were classified as having a low risk of bias (mean: 6.6★/7★). Thus, this study concluded that no significant association was identified between MIH and OHRQoL in Brazilian children. However, MIH may have a negative effect on the perception of oral symptoms in this population group.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".