Periodontal diseases in Down syndrome during childhood: a scoping review
Bibliographic record
Abstract
BACKGROUND: Down syndrome (DS) is a genetic condition that involves the deregulation of immune function and is characterized by a proinflammatory phenotype leading to an impaired response to infections. Periodontitis is a highly prevalent chronic inflammatory disease. It has been shown that adults and teenagers with DS are more susceptible to this disease, but a similar correlation in DS children remains elusive. This systematic scoping review aims to address this knowledge gap by examining periodontitis in DS children, with a secondary objective of elucidating the underlying mechanisms involved. METHODS: Our primary search was conducted via the PubMed/MEDLINE database and Google Scholar, covering the period from 1951-July 1st, 2024. Primary studies written in English or French were included. The excluded articles were reviews, in vitro or animal studies, studies on teenagers or adults, and studies involving patients with disabilities other than DS. The quality of evidence was assessed via the Newcastle‒Ottawa scale for observational studies and a published tool for evaluating the quality of case reports and case series. RESULTS: The initial electronic database search yielded a total of 2431 articles. 58 full-text articles, comprising seven cross-sectional studies, 36 case‒control studies, seven cohort studies, and eight case reports and case series, were included in the review. Compared with healthy children or children with disabilities, DS children appear to have more severe periodontal inflammation. However, the evidence is inconclusive regarding the presence of bone loss, with studies divided on this issue. Local risk and etiopathogenetic factors do not seem to play a significant role in increased inflammation. Instead, this difference could be attributed to the general proinflammatory phenotype of children with DS. CONCLUSIONS: DS children seem to have higher periodontal inflammation than other children, but no periodontal bone loss. Investigating periodontal inflammation in DS children could provide valuable insights into the deregulation of immune function in these patients.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".