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Record W2078441026 · doi:10.1111/jvim.12005

Effect of Canine Hyperadrenocorticism on Coagulation Parameters

2012· article· en· W2078441026 on OpenAlexafffund
Lara Rose, Marilyn E. Dunn, Christian Bédard

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversité de Montréal
FundersAssociation des Médecins Vétérinaires du Québec en Pratique des Petits Animaux
KeywordsMedicineThromboelastographyThrombin generationPopulationInternal medicinePlateletConfidence intervalCardiologyGastroenterologyThrombin

Abstract

fetched live from OpenAlex

BACKGROUND: Hyperadrenocorticism (HAC) has been associated with thrombotic disease in dogs. HYPOTHESIS: The purpose of this study was to use thromboelastography (TEG) and measurement of thrombin generation (TG) to characterize the hypercoagulable state in dogs with HAC. We hypothesized that dogs with HAC would have a hypercoagulable profile on TEG tracings and an increase in thrombin generation as measured by endogenous thrombin potential (ETP). ANIMALS: Sixteen dogs with HAC. Dogs were compared with a population of normal dogs used to obtain reference intervals. METHODS: TEG tracings on citrated whole blood were obtained from 15 dogs, and TG measurements on frozen-thawed platelet-poor plasma (PPP) were obtained from 15 dogs. RESULTS: For the TEG analysis, when results of individual dogs were compared with the reference interval, 12/15 dogs had at least 1 parameter associated with hypercoagulability. When the population of HAC dogs was compared with a population of healthy dogs, HAC dogs had decreases in R and K and increases in α and MA values. The ETP was increased when the HAC group was compared with a population of normal dogs. However, only 3/15 dogs had an ETP above reference interval, and 1/15 had a decreased lag time. CONCLUSION AND CLINICAL IMPORTANCE: Of 16 dogs with HAC, 12/15 had evidence of hypercoagulability when evaluated by TEG, 4/15 when evaluated by TG, and 2 dogs had increases in ETP and MA.

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)0.001
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 score0.538
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.047
GPT teacher head0.366
Teacher spread0.319 · 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

Citations45
Published2012
Admission routes2
Has abstractyes

Explore more

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