Out of hours management of occupational exposures to blood and body fluids in healthcare staff
Bibliographic record
Abstract
AIMS: To assess and compare the out of hours and in hours management of occupational blood and body fluid exposures in a London teaching hospital. METHODS: The occupational health and accident and emergency records of individuals presenting with occupational body fluid exposures over a six month period at a London teaching hospital were analysed retrospectively. Main outcome measures were the completeness of records, and the appropriate management of body fluid exposures using the Department of Health guidelines as the gold standard. RESULTS: A total of 177 body fluid exposures were reported; 109 (61.58%) were initially assessed in the occupational health department, and 68 (38.42%) in the accident and emergency department. Of those originally assessed in the accident and emergency department, only 21 (30.88%) attended the occupational health department for follow up. Occupational health staff were more consistent in assessing and managing exposures, and in a higher proportion of cases gave more appropriate advice on post-exposure prophylaxis (PEP) against hepatitis B and HIV. Of the 11 individuals prescribed HIV PEP (all by accident and emergency staff), only three subsequently attended occupational health for follow up. In all three cases therapy was discontinued, as the source was HIV negative or the exposure low risk. CONCLUSIONS: Out of hours management of occupational body fluid exposures, particularly the prescribing of HIV PEP, was inconsistent with in hours practice. This may also be the case in other large inner city hospitals offering a similar service.
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 | 0.010 |
| 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 | 0.000 |
| 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".