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Population pharmacokinetics of marbofloxacin in horses: preliminary analysis

2004· article· en· W2113321650 on OpenAlexaff
Mathieu Peyrou, Michèle Doucet, André Vrins, Didier Concordet, Marc Schneider, Alain Bousquet‐mélou

Bibliographic record

VenueJournal of Veterinary Pharmacology and Therapeutics · 2004
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsHorsePharmacokineticsMedicinePopulationCoefficient of variationRegimenVeterinary medicineInternal medicineBiologyChemistry

Abstract

fetched live from OpenAlex

Population pharmacokinetic of marbofloxacin was investigated on 21 healthy and 16 diseased horses to assess interindividual variability of drug exposure. Demographic, physiologic and disease covariables were tested using mixed effects models. As a preliminary analysis, this study has demonstrated that none of the tested covariables were significant in regression models for compartmental volumes or clearance of distribution, but the clinical status of the horse (healthy/diseased) was a significant covariable (P < 0.01) for systemic clearance. Clearance had a lower mean and a higher variance for diseased horses than healthy horses, with respectively a mean of 0.209 and 0.284 L/h/kg and a coefficient of variation of 52 and 15%. Consequently, variability of AUC was greater in diseased horses. Considering an AUC/MIC ratio below 60 h as a prediction of poor efficacy, a dosage regimen of 2 mg/kg intravenous was deemed to be inadequate for 19% of diseased horses if the MIC of the bacteria was 0.1 microg/mL. However 93% of diseased horses could achieve a ratio above 125 h, predicting a very good efficacy, for the MIC(90) of Enterobacteriacae (0.027 microg/mL).

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 score0.792
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.034
GPT teacher head0.364
Teacher spread0.329 · 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
Published2004
Admission routes1
Has abstractyes

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