Characterization of the oral microbiota and the relationship of the oral microbiota with the dental and periodontal status in children and adolescents with nonsyndromic cleft lip and palate. Systematic literature review and meta-analysis
Bibliographic record
Abstract
Abstract Objective To identify the characteristics of the oral microbiota and the relationship of the dental caries and periodontal status in patients aged 0 to 18 years with nonsyndromic cleft lip and palate (CLP).Material and methods A systematic review of the literature was carried out. Five databases were consulted, including publications in English, Spanish and Portuguese. The evaluations of the quality of the observational studies and the experimental studies were carried out with the Newcastle–Ottawa scale and CONSORT guidelines, respectively. The risk of bias of the studies was determined using Rev Manager 5.4, and 5 publications were meta-analyzed.Results In cariogenic microbiota, Lactobacillus spp. and Streptococcus mutans were identified at high levels, and the related periodontopathogenic microorganisms were Prevotella intermedia, Prevotella nigrescens, Porphyromonas gingivalis, Fusobacterium spp., Campylobacter spp., and Fusobacterium nigrescens. The microorganisms found in pre- and postoperative interventions were Staphylococcus aureus, Klebsiella pneumoniae, Klebsiella oxytoca, Streptococcus pyogenes, Moraxella catarrhalis, methicillin-resistant Staphylococcus aureus and Candida spp., with great heterogeneity in microbiological counts. The meta-analysis revealed that patients with CLP were 2.03 times more likely to have cavities than was the control group (p < 0.005).Conclusion In the microbiota, there was a great diversity of microorganisms that can vary according to the type of fissure and surgical interventions predisposing patients to a greater probability of dental caries.Clinical relevance To study the oral microbiota in CLP that facilitates the progression of dental caries and periodontal disease, take it into account in clinical decision-making and adopt preventive measures to reduce oral comorbidities.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".