External contamination of antineoplastic drug containers from a Canadian wholesaler
Bibliographic record
Abstract
INTRODUCTION: Contamination of hospitals' surfaces with antineoplastic drugs is documented despite safe handling practices. The exterior of commercial containers is often contaminated during the manufacturing process and can cross-contaminate hospitals' surfaces. The aim was to investigate the contamination of the exterior of antineoplastic drug vials available in Canada in 2018. METHODS: Cross-sectional study. All available antineoplastic drugs vials from a single wholesaler were targeted. Containers were sampled upon their receipt by the pharmacy staff, before they were cleaned. One wipe was used to sample the external surface of five vials from a single batch from the same manufacturer. Nine antineoplastic drugs were quantified by ultra-performance liquid chromatography-tandem mass spectrometer: cyclophosphamide, docetaxel, 5-fluorouracil, gemcitabine, ifosfamide, irinotecan, methotrexate, paclitaxel, vinorelbine. RESULTS: Twenty-one samplings were done (105 containers from nine different manufacturers): cyclophosphamide = 2, docetaxel = 1, gemcitabine = 2, 5-fluorouracil = 2, ifosfamide = 2, irinotecan = 3, methotrexate = 6, paclitaxel = 2, vinorelbine = 1. One of these samplings was done on blister packaging, the remainder were done on glass vials. A total of 15/21 samples (71%) were positive to at least one drug (docetaxel, 5-fluorouracil, ifosfamide, and vinorelbine). A maximum of 272 ng/vial was quantified (gemcitabine). Cross contamination with other antineoplastic drugs was detected on 16/21 (76%) samples. CONCLUSION: The majority of samples were positive to at least one antineoplastic drug, confirming that the exterior of antineoplastic drugs containers is still an important source of contamination. Manufacturers should reduce this contamination. Vials should be washed upon receipt, before they are stored in pharmacy. Gloves must be worn at all times to avoid occupational exposure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".