Association between early childhood oral health impact scale (ECOHIS) scores and pediatric dental surgery wait times
Bibliographic record
Abstract
BACKGROUND: Severe Early Childhood Caries (S-ECC) is an aggressive form of tooth decay that often requires pediatric dental rehabilitative surgery. The Early Childhood Oral Health Impact Scale (ECOHIS) measures oral health-related quality of life (OHRQL). The purpose of this study was to determine whether there is an association between ECOHIS scores and surgery wait times for children undergoing dental treatment for S-ECC under general anesthesia (GA). METHODS: The hypothesis was that there is no present association between wait times and ECOHIS score. Children under 72 months of age with S-ECC were recruited on the day of their slated dental surgery under GA. Parents/caregivers completed a questionnaire that included the ECOHIS. Data were merged with other ECOHIS scores from a previous study. Wait times were acquired from the Patient Access Registry Tool (PART) database. Data analysis included descriptive statistics and bivariate analyses. A p-value of ≤0.05 was considered statistically significant; 95% confidence intervals (CIs) were reported for each correlation coefficient. This study was approved by the University of Manitoba's Health Research Ethics Board. RESULTS: Overall, 200 children participated, the majority of whom were Indigenous (63%) and resided in Winnipeg (52.5%). The mean age was 47.6 ± 13.8 months and 50.5% were female. Analyses showed ECOHIS scores were not significantly correlated with children's wait times. Observed correlations between ECOHIS and children's wait times were low and not statistically significant, ranging from ρ = 0.11 for wait times and child impact section (CIS) scores (95% CI: - 0.04, 0.26; p = 0.14), ρ = - 0.08 for family impact section (FIS) scores (95% CI: - 0.23, 0.07; p = 0.28), and ρ = 0.04 for total ECOHIS scores (95% CI: - 0.11, 0.19; p = 0.56). CONCLUSION: No significant associations were observed between ECOHIS scores and wait times. In fact, those with worse OHRQL appeared to wait longer for surgery. ECOHIS scores could, however, still be used to help prioritize children for dental surgery to ensure that they receive timely access to dental care under GA. This is essential given the challenges posed by COVID-19 on timely access to surgical care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".