Emergency department visits for dental problems associated with trauma in Alberta: A report between the years 2011 and 2017
Bibliographic record
Abstract
BACKGROUND/AIMS: Dental trauma represents a significant cause for concern in emergency department (ED). The aim of this study was to report on the prevalence of ED visits for dental problems associated with trauma (DPAT) in Alberta, Canada. The specific objectives were to provide up-to-date information regarding ED utilization for dental trauma concerning the demographics of users and distribution of ED visits across the Province of Alberta, allowing for an assessment of possible trends over the period of time observed. METHODS: Data for ED visits in Alberta between January 1, 2011, and December 31, 2017, were extracted from the National Ambulatory Care Reporting System (NACRS). Data elements pertinent to this analysis include patient demographics, administrative information, and diagnosis. Only the main or primary diagnosis of each ED visit was included in this analysis using the International Statistical Classification of Diseases (ICD-10-CA). RESULTS: There were 71 118 total ED visits for DPAT in this time period, with an average of 10 159 visits per year across Alberta. Children aged 1-4 years old represented the age-group in both genders with the largest number of ED visits, 22.1% of the total number of visits. The number of ED visits for DPAT by males 21 years or younger (22 384) was higher than the total number of ED visits among females in all age-groups (21 099). The ICD-10-CA code S01.5 referring to open wound of lip and oral cavity was by far the most prevalent diagnosis, representing 57.6% of the total visits during the period investigated. CONCLUSIONS: This population-based report quantifies the rates and frequency of ED utilization for DPAT in the province of Alberta, Canada. The information gathered is important to support injury prevention initiatives using a population-based approach targeting the high-risk groups of the population identified by this study.
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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 | 0.001 | 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".