Pilot assessment of the antineoplastic drug contamination levels in British Columbian hospitals pre- and post-cleaning
Bibliographic record
Abstract
Objective. We undertook a pilot study involving six British Columbian hospital pharmacies to determine if antineoplastic drug contamination of surfaces exists and whether residual drugs remain on these surfaces despite being cleaned. Methods. At each site, the pharmacy technician responsible for preparing the antineoplastic drugs was observed to determine which surfaces were contacted and to ascertain the frequency of contact. Surfaces observed to be most frequently contacted were subsequently wiped after drug preparation pre- and post-clean. The wipe samples were then analyzed by liquid chromatography tandem mass spectrometry to determine the amount of contamination. Cyclophosphamide (CP) and methotrexate (MTX) were used as representative markers to reflect overall antineoplastic drug contamination levels. Results. Fourteen of the 23 surfaces sampled pre-clean (61%) were contaminated with either MTX or CP. The pre-clean wipe samples had a geometric mean concentration of 0.0135 ng/cm 2 for MTX (range 2 ) and 0.114 ng/cm 2 for CP (range 2 ). Post-clean contamination levels were generally lower than its pre-clean equivalent; the concentration difference post- vs. pre-clean was statistically significant for CP only. However, some samples appeared to have higher post-clean contamination levels. Conclusions. The results suggest that drug contamination is common in hospital pharmacies we sampled and that current cleaning practices in British Columbia may not be effective in removing residual drug from the surfaces. A more extensive study is recommended to confirm these results as well as a review of cleaning protocols to ensure their effectiveness in reducing contamination levels.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".