MétaCan
Menu
Back to cohort
Record W2604684461 · doi:10.1177/1040638717703434

Severe brachycephalic obstructive airway syndrome is associated with hypercoagulability in dogs

2017· article· en· W2604684461 on OpenAlexaboutno aff
Courtney A. Crane, Elizabeth A. Rozanski, Amanda L. Abelson, Armelle M. deLaforcade

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Conditions and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsThromboelastographyMedicineFibrinolysisObstructive sleep apneaHematocritAirwayClotting timeAnesthesiaCardiologyInternal medicinePlatelet

Abstract

fetched live from OpenAlex

We evaluated whether dogs with severe brachycephalic obstructive airway syndrome (BOAS) developed a hypercoagulable state similar to people with obstructive sleep apnea. Five dogs with grade 3 BOAS were included as well as 5 healthy control Labrador Retrievers. Venous blood samples were collected from each dog for performance of thromboelastography and determination of hematocrit and platelet count. Groups were compared using a t-test, with p < 0.05 considered significant. Thromboelastography results identified that all BOAS dogs were hypercoagulable compared to the Labradors, having significantly shortened clotting time with increased angle, maximal amplitude, and clot rigidity. BOAS dogs also had evidence of delayed fibrinolysis. These results are consistent with, but more severe than, those previously documented in apparently healthy Bulldogs. Together, these findings support the presence of a hypercoagulable state in brachycephalic dogs, and suggest that this state is amplified by increasing severity of BOAS.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.279
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Veterinary Diagnostic InvestigationSame topicCardiovascular Conditions and TreatmentsFrench-language works237,207