Quantification of healthcare workers’ exposure to cyclophosphamide, ifosfamide, methotrexate, and 5-fluorouracil by 24-h urine assay: A descriptive pilot study
Bibliographic record
Abstract
PURPOSE: The objective of this pilot study was to determine the frequency of urination and the concentration of four hazardous drugs (cyclophosphamide, ifosfamide, methotrexate, and fluorouracil) in workers' 24-h urine samples in relation to exposure to traces with hazardous drugs. METHODS: The study was conducted in three healthcare centers in the region of Montréal, Quebec, Canada. We recruited healthcare workers (nurses and pharmacy technicians) assigned to the hematology-oncology department. Each participant was asked to collect all urine voided during a 24-h period, to fill out an activity journal documenting tasks performed and to document the use of personal protective equipment. Samples were analyzed for cyclophosphamide, ifosfamide, methotrexate, and alpha-fluoro-beta-alanine (FBAL, the main urinary metabolite of 5-fluorouracil). Drugs were quantified by ultra-performance liquid chromatography-tandem mass spectrometry (positive electrospray MRM mode). RESULTS: Eighteen healthcare workers (10 nurses and 8 technicians) were recruited and provided consent to participate. Urine samples were obtained between 1 September and 30 September 2019. The number of urinations over the 24-h collection period ranged from 3 to 11 per participant. A total of 128 urine samples were analyzed for the 18 workers. All urine samples were negative for the four antineoplastics tested. CONCLUSION: No traces of cyclophosphamide, ifosfamide, methotrexate, or FBAL were found in the 24-h urine samples of 18 healthcare workers practicing in three healthcare facilities in Quebec. Although it was feasible to collect 24-h urine samples in this research project, it appears unrealistic to do so recurrently as part of a large-scale surveillance program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".