Trends in pediatric dental surgery for severe early childhood caries in Manitoba, Canada.
Bibliographic record
Abstract
INTRODUCTION: Caries is the most common chronic disease of childhood, and severe forms may necessitate rehabilitative dental surgery. In this study, administrative data related to pediatric dental surgery performed under general anesthesia to treat severe early childhood caries in Manitoba, Canada, were reviewed to determine trends in pediatric dental surgery, as well as geographic, regional and socio-economic variations in surgical rates. METHODS: The total number of dental surgery cases performed under general anesthesia was obtained from provincial administrative databases for fiscal years from 1997-98 to 2006-07. Codes from the International Classification of Diseases and Related Health Problems (9th or 10th revision, as appropriate) were used to identify children who underwent extractions under general anesthesia for a slightly earlier fiscal year period (1996-97 to 2005-06). Each 10-year period was divided into two 5-year periods for comparisons over time. Analyses included descriptive and bivariate statistics, with the data being disaggregated by regional health authority (RHA) or by community area (for Winnipeg). Comparisons for which p ≤ 0.05 were defined as statistically significant. RESULTS: A total of 18,544 children had dental surgery under general anesthesia between 1997-98 and 2006-07 (mean age ± standard deviation 3.28 ± 1.02 years). Many of the children requiring surgery resided in one northern RHA (26.8%) or the Winnipeg RHA (23.8%). More than half of the RHAs (7/11) displayed significant increases in the rate of surgery, with northern RHAs having the highest rates. Within Winnipeg, 3 of the 12 community areas had significant increases in the rate of surgery. Two inner-city neighborhoods accounted for nearly 50% of surgical cases. The rate of extractions under general anesthesia increased significantly in 6 of the 11 RHAs, with northern RHAs having the highest rates. Four Winnipeg communities experienced significant increases in the extraction rate over time. CONCLUSION: Pediatric dental surgery under general anesthesia for treatment of severe early childhood caries is common in Manitoba, and the demand increased in several communities over the study period. These results are being shared with decision-makers and communities to identify regions where oral health promotion is needed.
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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 | 0.002 | 0.006 |
| 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".