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Oral thermal injury associated with puncture of a salbutamol metered‐dose inhaler in a dog

2012· article· en· W1900269397 on OpenAlexaff
Shawn D. Mackenzie, Shauna L. Blois, Galina M. Hayes, Andrew R Vince

Bibliographic record

VenueJournal of Veterinary Emergency and Critical Care · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineAnesthesiaSalbutamolMetered-dose inhalerAirway obstructionTrismusPneumomediastinumLethargyVomitingStridorSubcutaneous emphysemaSurgeryInhalerAirwayComplicationAsthmaInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the clinical features, diagnostic work-up, treatment, and outcome of a dog with oral thermal injury secondary to chewing on a salbutamol metered-dose inhaler (MDI). CASE SUMMARY: A Boxer dog was presented after chewing on a salbutamol MDI. The dog was anxious, tachycardic and had moderate hypokalemia. The dog was treated with potassium supplementation and discharged after 24-hour hospitalization. Five hours after the discharge, the dog represented for dysphagia, anorexia, cervical pain, and a left-sided head tilt. Oral examination revealed edematous and erythematous swelling of the soft palate causing airway compromise; histopathology demonstrated vascular necrosis and infarction. The dog was treated with supportive care including the placement of a tracheostomy tube. The dog recovered fully and was discharged 8 days after initial presentation. NEW OR UNIQUE INFORMATION PROVIDED: Salbutamol toxicity has been documented previously in dogs but oral thermal injury associated with a salbutamol MDI has not been reported in dogs. Although a rare complication, dogs who have been exposed to MDIs should have a thorough oral exam and be monitored closely for signs of respiratory compromise.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.808

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)0.0010.000

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 head0.045
GPT teacher head0.328
Teacher spread0.284 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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