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Record W2261506586 · doi:10.1111/jvp.12293

The pharmacokinetics of DPH after the administration of a single intravenous or intramuscular dose in healthy dogs

2016· article· en· W2261506586 on OpenAlexaff
Andrea Sánchez, Alexander Valverde, M. Sinclair, Cornelia Mosley, Ameet Singh, Anthony J. Mutsaers, Brad Hanna, Yongan Gu, Ron J. Johnson

Bibliographic record

VenueJournal of Veterinary Pharmacology and Therapeutics · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPharmacokineticsDiphenhydramineBioavailabilitySedationPlasma concentrationMedicinePharmacologyAdverse effectAnesthesiaChemistryHistamine

Abstract

fetched live from OpenAlex

The objective of this study was to determine the pharmacokinetics of diphenhydramine (DPH) in healthy dogs following a single i.v. or i.m. dose. Dogs were randomly allocated in two treatment groups and received DPH at 1 mg/kg, i.v., or 2 mg/kg, i.m. Blood samples were collected serially over 24 h. Plasma concentrations of DPH were determined by high-performance liquid chromatography, and noncompartmental pharmacokinetic analysis was performed with the commercially available software. Cardio-respiratory parameters, rectal temperature and effects on behaviour, such as sedation or excitement, were recorded. Diphenhydramine Clarea , Vdarea and T1/2 were 20.7 ± 2.9 mL/kg/min, 7.6 ± 0.7 L/kg and 4.2 ± 0.5 h for the i.v. route, respectively, and Clarea /F, Vdarea /F and T1/2 20.8 ± 2.7 mL/kg/min, 12.3 ± 1.2 L/kg and 6.8 ± 0.7 h for the i.m. route, respectively. Bioavailability was 88% after i.m. administration. No significant differences were found in physiological parameters between groups or within dogs of the same group, and values remained within normal limits. No adverse effects or changes in mental status were observed after the administration of DPH. Both routes of administration resulted in DPH plasma concentrations which exceeded levels considered therapeutic in humans.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.378
Teacher spread0.303 · 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 designBench or experimental
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

Citations9
Published2016
Admission routes1
Has abstractyes

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