Risk Indicators and Treatment Needs of Children 2–5 Years of Age Receiving Dental Treatment under General Anesthesia in Saskatchewan
Bibliographic record
Abstract
Background: When compared to national averages in Canada, Saskatchewan has one of the highest rates of dental treatment under general anesthesia (GA) and average costs per child. Thus, the purpose of this cross-sectional study is to explore the risk indicators and treatment needs of children receiving dental treatment under GA in Saskatchewan. Methods: In this cross-sectional study, we recruited caregivers of children between 24 and 71 months of age in Saskatoon, Canada. Caregivers completed a 40-item questionnaire, which was supplemented with clinical data and then subject to statistical analysis (independent t-tests and one-way ANOVA). Results: A total of 90 caregiver/child dyads were enrolled with the mean age for children being 49.5 ± 12.3 months. The mean age of a child’s first dental visit was 34.7 ± 15.3 months with only 37.9% of children having a dental home. The mean deft index was 11.7 ± 3.4, with an average of 10.9 ± 3.5 teeth receiving treatment. Additionally, location of primary residence (p = 0.03), family income (p = 0.04), family size (p = 0.01), parental education (p = 0.03), dental home (p = 0.04), and body mass index (p = 0.04) had a statistically significant association with a higher mean deft. Conclusions: Our cross-sectional study confirms that children who require dental treatment under GA have a high burden of disease. While individual risk indicators such as diet and oral hygiene play a role in the progression of early childhood caries (ECC), we also demonstrate that children who do not have access to early preventive visits or a dental home are at a higher risk. In addition to improving motivation for oral hygiene at home and nutritional education, improving access to oral health care should be addressed in strategies to reduce ECC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".