A Meta-Analysis of Oral Health Status of Children with Autism
Bibliographic record
Abstract
Purpose: To present a meta-analysis whether the risks of caries and periodontal problems in autistic children are higher than those in healthy children. Study design: A literature search that included PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure (CNKI), Wan fang, and Chinese Scientific and Technological Journal (VIP) databases was conducted. The primary outcomes of interest included the DMFT index, Plaque index (PI), Gingival index (GI), and Salivary pH. Quality assessment was performed in accordance with the Newcastle-Ottawa Scale (NOS). Dichotomous variables are presented as relative risk (RR), and continuous variables are presented as weighted mean difference (WMD). Results: Eight studies were included in this meta-analysis. Among these 8 studies, six studies compared the DMFT index, three studies compared PI, three studies compared GI, and three studies compared salivary pH. Meta-analysis showed that the mean DMFT index in autistic children was higher than that in healthy children, and the difference was statistically significant {MD = 0.50, 95% CI [0.04–0.96], P<0.00001}. Similarly, PI and GI in autistic children were higher than those in healthy children, and the difference between PI was statistically significant {MD = 0.59, 95%CI [0.36–0.82], P=0.02}, while the difference between GI was not statistically significant {MD = 0.52, 95%CI [0.30–0.75], P=0.08}. But the salivary pH in autistic children was lower than that in healthy children {MD = −0.28, 95%CI [−0.54–−0.02], P = 0.02}, and the difference was statistically significant. Conclusion: The present analysis suggests that children with autism have poorer oral hygiene, higher risk of caries, and a lower salivary pH than healthy children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.063 |
| Bibliometrics | 0.008 | 0.005 |
| 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) | 0.003 | 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".