Screening for alcohol and drug use in pediatric trauma
Bibliographic record
Abstract
Background: Level 1 pediatric trauma centres should screen all trauma patients aged 12 years and older for alcohol use and provide substance use interventions as a means to minimize relapse. We aimed to approximate the rate of alcohol and drug use screening in Canadian pediatric patients admitted for trauma in our centre, determine the prevalence of intoxication on admission and compare the injury characteristics and morbidity of patients with and without concomitant substance use. Methods: We conducted a single-centre retrospective review of the Stollery Children’s Hospital’s medical records abstracted from the Alberta Trauma Registry database of patients aged 12–17 years who were admitted for trauma (Injury Severity Score ≥ 12) between Jan. 1, 2012, and Dec. 31, 2021. Results: Of the 543 patients included in the analysis, 380 (70.0%) received screening for alcohol as a part of their trauma panel; meanwhile, only 5 (0.9%) patients were screened for drug use. Among the patients who were screened for alcohol, 47 (12.4%) had a positive blood alcohol level (BAC). Nine (7%) of 129 screened patients aged 12–14 years were found to have positive BACs compared with 38 (15.1%) of 251 screened patients aged 15–17 years. Patient age and mechanism of injury significantly affected rates of screening. Among patients with positive BACs on admission, the 3 most prevalent mechanisms of injury were motor vehicle accident (26 [55.3%]), assault (13 [27.7%]) and recreational vehicle accidents (4 [8.5%]). Patients with a positive BAC sustained significantly more severe injuries (p = 0.003). Conclusion: These results provide evidence of the importance of standardized screening to identify pediatric patients admitted for trauma who are in need of treatment for alcohol and drug use. The Screening, Brief Intervention and Referral to Treatment model is the primary approach used to fulfill substance use identification and intervention recommendations. The Alcohol Use Disorders Identification Test and the Car, Relax, Alone, Forget, Friends, Trouble questionnaire are most suitable for adolescent populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".