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Record W7045421870

Asthma and Epinephrine Administration Prior to Emergency Department Presentation for Suspected Anaphylaxis in Pediatric Patients

2022· other· en· W7045421870 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsnot available
Fundersnot available
KeywordsAnaphylaxisEpinephrineAsthmaEmergency departmentAllergyLogistic regression
DOInot available

Abstract

fetched live from OpenAlex

Anaphylaxis is a potentially life-threatening systemic allergic reaction that involves at least two organs or systems and may result in hypotension. The mainstay of anaphylaxis treatment is epinephrine, and as such, individuals with severe allergies are recommended to carry epinephrine auto-injectors (EAIs). However, there is a substantial underutilization of EAIs for the management of anaphylaxis. One of the challenges that hinders early anaphylaxis diagnosis and management is its similarity to asthma with respect to immunopathology, clinical presentation, response to therapies, and natural history. While asthma and anaphylaxis frequently coexist and mimic each other, the exact influence of the two conditions on each other has yet to be fully explained. In the current study using data from the Cross-Canada Anaphylaxis registry (C-CARE), univariable and multivariable logistic regressions were performed to examine the association between comorbid asthma and both pre-hospital and overall epinephrine treatment. It was identified that the presence of comorbid asthma asthma was not associated with the use of pre-hospital epinephrine in the treatment of anaphylaxis and is associated with a decreased likelihood of receiving epinephrine overall. Given this finding, and the current substantial underutilization of EAIs, it is more important than ever to improve EAI prescribing practices and educate patients with allergies and relevant caregivers on prompt and safe EAI use.

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 score0.578
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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