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Record W1966812025 · doi:10.3747/co.21.2151

Safe Handling of Cytotoxics: Guideline Recommendations

2015· article· en· W1966812025 on OpenAlexaffvenue
Anthony Easty, N. Coakley, Ryan R. Cheng, Maureen Cividino, Pamela Savage, Richard Tozer, Rachel E. White

Bibliographic record

VenueCurrent Oncology · 2015
Typearticle
Languageen
FieldHealth Professions
TopicSafe Handling of Antineoplastic Drugs
Canadian institutionsPrincess Margaret Cancer CentreJuravinski HospitalMcMaster UniversityCancer Care OntarioSt. Joseph’s Healthcare HamiltonPublic Health OntarioUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineGuidelineIntensive care medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: This evidence-based practice guideline was developed to update and address new issues in the handling of cytotoxics, including the use of oral cytotoxics; the selection and use of personal protective equipment; and treatment in diverse settings, including the home setting. METHODS: The guideline was developed primarily from an adaptation and endorsement of an existing guideline and from three systematic reviews. Before publication, the guideline underwent a series of peer and external reviews to gather feedback. All comments were addressed, and the guideline was amended when required. The guideline applies to health care workers who could come into contact with cytotoxic drugs at any point in the medication circuit. The intended users are hospital administrators, educators, and managers; occupational health and safety services; and pharmacy and health care workers. RESULTS: The recommendations represent a reasonable and practical set of procedures that the intended users of this guideline should implement to minimize opportunities for accidental exposure. They are not limited to just the point of care; they cover the entire chain of cytotoxics handling from the time such agents enter the institution until they leave in the patient or as waste. CONCLUSIONS: Reducing the likelihood of accidental exposure to cytotoxic agents within the medication circuit is the main objective of this evidenced-based guideline. The recommendations differ slightly from earlier guidelines because of the availability of new evidence.

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 imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.090
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0090.007
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0090.003
Research integrity0.0130.009
Insufficient payload (model declined to judge)0.0090.005

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.

Opus teacher head0.432
GPT teacher head0.583
Teacher spread0.151 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations70
Published2015
Admission routes2
Has abstractyes

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