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Discoloration of Parenteral Ondansetron

2003· article· en· W2067624555 on OpenAlexaff
Ban C. H. Tsui, Dominic Cave

Bibliographic record

VenueAnesthesia & Analgesia · 2003
Typearticle
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsOndansetronMedicineVialPharmacyAnesthesiaSyringeNoticeDrug packagingSurgeryNauseaNursing

Abstract

fetched live from OpenAlex

To the Editor: We would like to report a rare problem we experienced with parenteral ondansetron (GlaxoWellcome). We have used ondansetron routinely for more than five years in our institutions. For the first time, we noticed 2 bottles of discolored ondansetron dispensed to the OR from the pharmacy along with other clear bottles of ondansetron with the same lot number and expiration date (Figure 1).Figure 1: Discoloration of Ondansetron. Ondansetron with the same lot number and expired date in the original bottles and draw up in 3ml plastic syringes. (Top) normal clear ondansetron. (Bottom) discolored ondansetron.Manufacturer’s instructions recommend discarding any discolored bottle of ondansetron. Although compliance with this instruction is obvious, the cause of the discoloration is not immediately apparent. Nor is it always easy for the anesthesiologist to detect discoloration of medication as they often work and administrate medications under poor lighting conditions, such as during laparoscopic surgery. Discoloration is even more difficulty to notice if the drug is already drawn into a plastic syringe (Figure 1), and the degree of discoloration may vary between vials. This would create the impression of a discolored vial and a clear vial, when the true situation was one strongly discolored and one less so. Fortunately, we detected the discolored medication prior to administration to our patient in a properly lit OR. This experience serves to remind us of the importance of carefully examining all medications under adequate lighting prior to administration. Ban C. H. Tsui, MSC, MD, FRCP(C) Dominic Cave, MBBS, FRCP(C)

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.266
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2003
Admission routes1
Has abstractyes

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