Quantification of healthcare workers’ exposure to cyclophosphamide, ifosfamide, methotrexate, and 5-fluorouracil by 24-h urine assay: A descriptive pilot study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it