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Record W7042832494

Prevalence of Echocardiographic Evidence of Trace Mitral and Aortic Valve Regurgitation in 50 Clinically Healthy, Young Adult Labrador Retrievers without Heart Murmur

2022· article· en· W7042832494 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2022
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRegurgitation (circulation)Mitral regurgitationHeart murmurMitral valveAuscultationDoppler echocardiographyYoung adultAortic valve
DOInot available

Abstract

fetched live from OpenAlex

Background-Though physiologic regurgitation of the right-sided cardiac valves is well recognized in dogs and other mammals, the prevalence of trace insufficiency of the mitral and aortic valves in clinically healthy, young adult dogs is unknown. Methods-In this observational cross-sectional study, 50 clinically healthy, young adult Labrador retrievers without an audible heart murmur were enrolled. All dogs were bred and owned by a single organization. Cardiac screening was requested for all dogs that were intended for breeding. These dogs underwent a cardiac auscultation and transthoracic echocardiography by a veterinary cardiology specialist. If mitral or aortic valve regurgitation was noticed, the jet size was subjectively assessed on color Doppler echocardiography. Pedigree analysis was performed to reveal a possible hereditary background of mitral valve regurgitation. Results-The prevalence of trivial mitral valve regurgitation was 52% with no significant predisposition to gender ( p = 0.86) or haircoat color ( p = 0.68). The prevalence of aortic valve regurgitation was 4%. Pedigree analysis for mitral valve regurgitation showed familial clustering, suggesting a hereditary background of the trait. Conclusions-The prevalence of silent trace mitral valve regurgitation in young adult Labrador retrievers was high. Because the regurgitant jet was trivial in all dogs, it is probably physiologic.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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.

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

Explore more

Same venueUtrecht University Repository (Utrecht University)Same topicHigh Entropy Alloys StudiesFrench-language works237,207