Use of personal protective equipment in a radiology room at a veterinary teaching hospital
Bibliographic record
Abstract
The use of personal protective equipment by veterinary workers during radiographic imaging is inconsistent. While the self-reported use of leaded aprons and thyroid shields approaches 100% in some studies, the use of leaded gloves and eyeglasses is much lower. Previous studies describing personal protective equipment use are based on self-reporting. Objectives of this prospective, observational study were to describe use of leaded personal protective equipment during radiographic imaging by veterinary workers, and to compare observed use with self-reported use. Use of leaded personal protective equipment during radiographic imaging by veterinary workers was observed over a 10 week period using two motion-triggered video cameras, and a questionnaire was then completed by workers on their use of personal protective equipment. Workers restrained the animal during 91.8% (753/820) of exposures. An apron and a securely closed thyroid shield were worn for >99% of studies. Gloves were used correctly for 43.6% (156/358) of radiographic studies. Leaded eyeglasses were worn for 1.7% (6/358) of studies. Correct glove use was more frequent during regular working hours than after-hours for both veterinarians (odds ratio 32.7, P = 0.001) and veterinary students (odds ratio 75.1, P < 0.001). The number of workers in the room was lower when animals were sedated (P = 0.002) or anesthetized (P = 0.017). Workers overestimated their frequency of glove use (P <0.001). In conclusion, workers use personal protective equipment less frequently in an unsupervised environment, and overestimate their use of personal protective equipment. Use of sedation or anesthesia decreases worker exposure to ionizing radiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".