Community-acquired needle stick injuries in Canadian children: Review of Canadian Hospitals Injury Reporting and Prevention Program data from 1991 to 1996
Bibliographic record
Abstract
OBJECTIVE: To review community-acquired needle stick injuries (CANSIs) in children reported to a Canadian emergency room-based injury surveillance program. DESIGN: Analysis of 1991 to 1996 CANSI records followed by chart review to determine use of prophylactic interventions and outcome information. SETTING: The Canadian Hospitals Injury Reporting and Prevention Program network of 10 paediatric and six general hospitals. PATIENTS: Nonoccupational injuries to patients younger than age 20 years involving used needles were reviewed. MAIN RESULTS: Of 116 children injured, most were male (74%); the median age was 6.6 years. Needles were picked up before injury in 77% of the cases. Most injuries (78%) were from needles presumed to have been discarded by an injection drug user. Parks were the most common site of injury (21%). Six per cent of injuries occurred in medical settings. Treatment information was obtained for 71 (61%) patients. Only 1.7% had been immunized against hepatitis B virus before injury. Hepatitis B immune globulin and hepatitis B virus vaccine were given to 78% and 76% of children, respectively. None received human immunodeficiency virus prophylaxis. CONCLUSIONS: Programs teaching needle avoidance may help prevent many CANSIs. The safety of outdoor, home and medical environments also needs to be ensured. Treatment guidelines for CANSIs will help ensure appropriate postinjury management.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".