Relationship between type-I diabetes mellitus and oral health status and oral health-related quality of life among children of Saudi Arabia
Bibliographic record
Abstract
Introduction: The study was conducted to assess the impact of oral health status on the oral health-related quality of life (OHRQOL) of children between 12 and 15 years with type-1 diabetes mellitus (IDDM) in Saudi Arabia and compare these findings to age and gender matched medically fit children. Materials and Method: A total of 40 children aged between 12 and 15 years with (IDDM) group presenting to the pediatric endocrinology clinic of the KSMC, Riyadh were age and gender matched to a control group of children reporting for a routine dental checkup at the dental clinics of the REU. The oral health of all children was recorded using WHO examination criteria. Parental perception of the OHRQoL was recorded using the validated Arabic version of the short-form child oral health impact profile—short-form COHIP-19. The independent samples t-test was used to compare the DMFT, Gingival index, and COHIP19 domains of the two groups. Results: Individuals with IDDM had higher Gingival Index and DMFT scores; however, the differences were not statistically significant. The IDDM group showed higher COHIP scores across all domains. However, the differences were only statistically significant for the oral health domain (P = 0.003). Conclusion: Children with IDDM had better oral health both in terms of dental caries and gingival status when compared to their age-matched controls. However, they had significantly higher oral health domains that suggest a poorer overall OHRQoL in children with IDDM.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".