Sharps-handling practices among junior surgical residents: a video analysis
Bibliographic record
Abstract
BACKGROUND: Although "universal precautions" are standard for sharps handling, there has been poor compliance among surgeons. We used video analysis to assess sharps handling practices among junior surgical residents. METHODS: Postgraduate year (PGY)-2 general surgery and PGY-1 plastic surgery residents were videotaped performing pediatric inguinal hernia repairs. For each procedure, the resident was the principal operator, with the attending surgeon assisting. Retrospective assessment of safe and unsafe sharps handling was determined based on published guidelines. We assessed safety performance in personal sharps tasks, passage of sharps and verbal notification regarding sharps. Data was analyzed using descriptive statistics. RESULTS: Data were collected from 18 residents' videos (4 plastic surgery, 14 general surgery). Residents safely performed sharps tasks, passed and verbally notified about sharps an average of 69.2%, 93.2% and 9.9% of the time, respectively. Suture needle manipulation was handled safely 56.2% of the time (mean 4.4 safe v. 4.3 unsafe actions). Surgical residents demonstrated a safe suture tying technique in 91.8% of cases, proper tissue retraction in 85.2% and safe handling of injection needles in 72.2% of cases. When assessing the safety performance of the surgical team, attending surgeons acting as surgical assistants safely passed sharps 80.0% of the time, while scrub nurses demonstrated safe passing at all times. Attending surgeons used verbal notification when passing sharps 22.7% of the time, while scrub nurses verbally notified the team 4.3% of the time. CONCLUSION: Junior surgical residents consistently passed sharps safely. Personal sharps tasks were less likely to be performed safely, and only a minority of residents verbally notified the team about sharps placement.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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 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".