The use of general anesthesia for dental treatment of children with special healthcare needs in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Children with special healthcare needs (SHCN) often require specialized interventions due to their disabilities. Dental general anesthesia (DGA) is a treatment modality, which improves their access to care but concerns about repeated DGAs persist. AIM: This study investigated DGA utilization in children with SHCN and identified factors associated with multiple DGAs in Alberta, Canada (2010-2020). DESIGN: This retrospective population-based study used administrative data encompassing all children (<18 years) undergoing DGA in publicly funded facilities. Children were identified as SHCN based on their diagnosis codes and categorized into behavioral/psychiatric disorders, mental/intellectual disabilities, physical disabilities, systemic conditions, syndromes/congenital anomalies, physical-mental disabilities, and disabilities with medical conditions. RESULTS: This study analyzed 3884 DGA visits for children with SHCN, predominantly males aged 6-11 and from low-income families. Mental/intellectual disabilities were prevalent (31.8%), and autism was the leading disease. Caries was the primary dental diagnosis across all groups, whereas pulp problems were higher in psychiatric/behavioral disorders (23.6%), and periodontal problems were more common in physical-mental disabilities (13.2%). 28.7% had multiple DGAs, with younger age, disabilities with medical conditions, mental/intellectual disabilities, and initial pulp treatments, increasing the likelihood of multiple DGAs. CONCLUSION: This study highlights the importance of individualized prevention and less conservative treatments for younger children to reduce oral health disparities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".