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Effect of Pimobendan on Echocardiographic Values in Dogs with Asymptomatic Mitral Valve Disease

2009· article· en· W2025190963 on OpenAlexaff
Mathieu Ouellet, Myriam Bélanger, Rocky DiFruscia, Guy Beauchamp

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Conditions and Treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineAsymptomaticCardiologyInternal medicineEjection fractionMitral regurgitationHemodynamicsMitral valveHeart failure

Abstract

fetched live from OpenAlex

BACKGROUND: Pimobendan (PIMO) is a novel inodilator that has shown promising results in the treatment of advanced mitral valve disease (MVD), but little is known about its hemodynamic effects, especially regarding the mitral regurgitant volume in naturally occurring MVD. HYPOTHESIS: The addition of pimobendan to treatment decreases the regurgitant fraction (RF) in dogs with asymptomatic MVD. ANIMALS: Twenty-four client-owned dogs affected by International Small Animal Cardiac Health Council class Ib MVD. METHODS: Prospective, blinded, and controlled clinical trial. Dogs were assigned to a PIMO treatment group (n = 19) (0.2-0.3 mg/kg q12h) or a control group (n = 5). Echocardiographic evaluations were performed over a 6-month period. RESULTS: The addition of PIMO to treatment did not decrease the RF of dogs affected by asymptomatic class 1b MVD over the study period (P= .85). There was a significant increase in the ejection fraction of the PIMO treated dogs at 30 days (80.8 +/- 1.42 versus 69.0 +/- 2.76, corrected P= .0064), and a decrease in systolic left ventricular diameter (corrected P= .011) within the PIMO group compared with baseline. However, this improvement in systolic function was not sustained over the 6-month trial period. CONCLUSION AND CLINICAL IMPORTANCE: This study did not identify beneficial long-term changes in the severity of mitral regurgitation after addition of PIMO to angiotensin converting enzyme inhibitor treatment of dogs with asymptomatic MVD.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.010
GPT teacher head0.306
Teacher spread0.296 · 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

Citations28
Published2009
Admission routes1
Has abstractyes

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