Comparison of oral indices in patients with Down syndrome and healthy individuals: A meta-analysis study
Bibliographic record
Abstract
ABSTRACT Background: The aim of the present study was to compare dental indexes of pediatric Down syndrome (DS) patients to those who are healthy. Materials and Methods: This study was carried out based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement guidelines. The researchers searched title and abstract of major databases, including ProQuest (ProQuest Dissertations and Theses Full Text: Health and Medicine, ProQuest Nursing and Allie Health Source), PubMed, Google Scholar, clinical key, up to date, springer, Cochrane, Scopus, Embase, and Web of Science (ISI), up to September 2020 with restriction to English and Persian language This meta-analysis study had three outcomes: decay/miss/filled index, plaque index, and gingival index. Effect size, including mean difference and its 95% of confidence interval, was calculated. The Newcastle–Ottawa Scale measured the quality of the selected studies. Heterogeneity was performed using the Q test and I 2 index, and reporting bias was assessed using a funnel plot and Egger and Begg’s tests. Results: Fifteen studies conducted were included in the meta-analysis process. Conclusion: It showed that DS patients had a higher plaque index and gingival index than healthy individuals, which means that the oral health status of these patients is worse and needs more attention.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".