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Record W2114561119 · doi:10.1111/vec.12361

Pneumothorax in a dog caused by necrotizing pneumonia secondary to heatstroke

2015· article· en· W2114561119 on OpenAlexaboutno aff
Jocelyn B. Garber, Katrin Saile, Nathalie Rademacher, James R. Wignall, Leslie D. McLaughlin, Kirk A. Ryan

Bibliographic record

VenueJournal of Veterinary Emergency and Critical Care · 2015
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePneumothoraxPneumoniaSurgeryComplicationLungInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the clinical course, diagnostic findings, medical and surgical treatments, and outcome in a dog with spontaneous pneumothorax secondary to necrotizing pneumonia thought to be a delayed complication of heatstroke. CASE SUMMARY: A 1.5-year-old Labrador Retriever developed spontaneous pneumothorax 12 days after an episode of exertional heat stroke. Computed tomography was performed and showed bilateral pneumothorax and multifocal pulmonary consolidation, especially at the lung periphery. A median sternotomy was performed, and multifocal, well-demarcated areas of consolidated pulmonary tissue with purple discoloration were identified and resected from the right middle, right caudal, and accessory lung lobes. Histologic examination of the resected pulmonary tissue indicated necrotizing pneumonia, and bacteriologic culture of the tissue resulted in growth of Pseudomonas aeruginosa. Examination of tissue from a pectoral muscle biopsy performed at this time showed necrotizing myopathy. The dog was discharged 7 days after surgery and made a full recovery. NEW OR UNIQUE INFORMATION PROVIDED: This case report describes pneumothorax and multifocal necrotizing pneumonia as a delayed complication of heatstroke, and provides the first description of the computed tomography appearance of histologically confirmed necrotizing pneumonia in a dog. Multifocal necrotizing pneumonia with or without pneumothorax should be considered in dogs that develop respiratory distress following severe systemic illness.

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 score0.516
Threshold uncertainty score0.520

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 head0.053
GPT teacher head0.358
Teacher spread0.305 · 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
Published2015
Admission routes1
Has abstractyes

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