Nontraumatic Dental Complaints in a Pediatric Emergency Department
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence, types, and treatment of nontraumatic dental emergencies that present to a tertiary care pediatric emergency department (ED). METHODS: A retrospective chart review of all children coming to a tertiary care pediatric emergency department with nontraumatic dental complaints from January 2005 to December 2005 was conducted. Demographic information, the time and day of presentation, presenting complaints, history of previous dental treatment, interventions, and disposition details were collected and analyzed. RESULTS: The 247 visits for nontraumatic dental complaints comprise 0.5% of all patients who presented to the ED in 2005. Fifty-nine percent were younger than 5 years (primary dentition), with males representing 52% of the children. Half of the visits were during normal dental office hours, and more than half presented during the weekday. Fifty-three percent complained of pain. Twenty-eight percent were referred to the dental clinic after being seen by an ED physician. Eight percent of children required hospitalization for intravenous antibiotics. Most children (82%) were discharged from the ED with oral antibiotics. CONCLUSIONS: The ED is an important point of care for nontraumatic pediatric dental complaints, and about 60% of these children are younger than 5 years. Only 8% of them had severe infections requiring hospitalization, and most patients could have been treated in the community.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".