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Record W4403058891 · doi:10.58931/cait.2023.3359

Epinephrine auto-injectors in Canada: A review of available products and clinical proposals

2023· review· en· W4403058891 on OpenAlexaffabout
Harold Kim, Graham Walter

Bibliographic record

VenueCanadian allergy & immunology today. · 2023
Typereview
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsMcMaster UniversityUniversity of ManitobaWestern University
Fundersnot available
KeywordsEpinephrineMedicineBusinessPolitical scienceAnesthesia

Abstract

fetched live from OpenAlex

Anaphylaxis is a severe reaction with significant associated morbidity and mortality that necessitates prompt on-demand management for patients. Epinephrine administered intramuscularly at a dose of 0.01 mg/kg of body weight, up to a maximum single dose of 0.5 mg at one time, is the first-line treatment for anaphylaxis. Epinephrine auto-injectors (EAIs) are devices designed to deliver a predetermined dose of epinephrine rapidly and reliably into the vastus lateralis muscle of the mid-anterolateral thigh for treatment of anaphylaxis. All commercially available auto-injectors in Canada are fixed-dose delivery systems, therefore titration of epinephrine dose based on patient weight is not possible. In Canada, there are several manufacturers of EAIs, providing treating physicians and patients with a variety of options to treat anaphylaxis in the community. However, as these devices all contain the same medication, physicians may not realize that specific EAIs may be of greater utility in certain clinical circumstances. This scientific review aims to describe all currently available EAIs in Canada, with detailed discussion on the differences between products and the nuances of a patient-centred approach to prescription in a market filled with seemingly “one size fits all” devices.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.791
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.331
Teacher spread0.258 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes2
Has abstractyes

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