Oral Microbiota in Children with Cleft Lip and Palate: A Systematic Review
Bibliographic record
Abstract
Background: Cleft in the lip and/or palate (CLP) is a congenital facial deformity that significantly impacts the oral cavity’s structure and function. This malformation can affect the oral microbiota. The objective of this systematic review was to examine and consolidate the current scientific evidence on the oral microflora in children with CLP. Methods: The search strategy included the PubMed, PubMed Central, Web of Science, Scopus, and Embase databases. The inclusion criteria were studies assessing oral microbiota in children with CLP. The Newcastle–Ottawa Scale (NOS) was used to evaluate the quality of the included studies. Results: The search strategy identified 422 potential articles. Twelve papers met the inclusion criteria. High heterogeneity was observed in methodologies, sample sites, and patient characteristics. Eight studies assessed the levels of Streptococcus mutans and Lactobacillus in saliva, with some reporting significantly higher levels in the cleft group compared to controls, while others found no differences. One study reported a significantly higher colonization rate of Candida species in patients with cleft lip and/or palate. Conclusion: The results of the available studies are unclear. Further research is needed to gain a comprehensive understanding of the oral microbiota and potential implications for oral health management in this population. The review was not registered Registration Statement.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".