The Use of General Anesthesia for Pediatric Dentistry in Saskatchewan: A Retrospective Study.
Bibliographic record
Abstract
INTRODUCTION: The rate of general anesthesia (GA) use for pediatric dental treatment in Saskatchewan is among the highest in Canada. Although the prevalence of and risk factors for early childhood caries (ECC) has been reviewed nationally, few studies have focused on Saskatchewan. The objective of this study was to determine the prevalence of and predictive factors for dental treatment under GA in Saskatchewan. METHODS: This retrospective review focused on pediatric patients who required dental treatment under GA in Saskatchewan between 2015 and 2018. Demographic, dental diagnostic and treatment data and number of previous exposures to GA were collected and analyzed. RESULTS: We reviewed 570 patient records. Dental treatment needs among the sample were complex; children had 10.85 ± 3.56 (mean ± standard deviation) teeth treated, for an average cost of $3231.72 ± $898.95 per child. Children who lived in less accessible or remote locations had a significantly higher caries experience, number of teeth treated and cost of treatment. In addition, children who lived in such locations were more likely to have had previous dental treatment under GA (odds ratio [OR] 1.29, 95% CI 1.029-1.645) compared with those who lived in easily accessible/accessible areas (OR 0.81, 95% CI 0.700-0.953). CONCLUSION: Our findings confirm previous research that children who require dental treatment under GA have extensive caries and treatment needs. Our results suggest that children who live in less accessible and more remote areas of the province have a higher burden of disease and are more likely to require repeated GA exposures for dental treatment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".