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Evaluation of dirlotapide for sustained weight loss in overweight Labrador retrievers

2007· article· en· W2016501684 on OpenAlexaboutno aff
J. Gossellin, S. Peachey, J. Sherington, T.G. Rowan, S. Sunderland

Bibliographic record

VenueJournal of Veterinary Pharmacology and Therapeutics · 2007
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
FundersPfizer
KeywordsWeight lossOverweightPlaceboAnimal scienceMedicineBody weightLean body massObesityInternal medicineBiology

Abstract

fetched live from OpenAlex

The effects of dirlotapide on body weight (BW) reduction were investigated in overweight Labradors in two parallel-design studies. Study A involved 42 dogs randomized to 0.0, 0.025, 0.05, 0.1, 0.2 or 0.4 mg dirlotapide/kg/day orally for 4 weeks. Study B involved 72 dogs randomized to nine treatments: placebo (24 weeks); dirlotapide (24 weeks) followed by placebo (28 weeks); or dirlotapide (52 weeks); on diets containing 5%, 10% or 15% fat. Dirlotapide dose (initially 0.1 mg/kg) was adjusted monthly during 24-week weight-loss and subsequent 28-week weight-stabilization phases. Food was offered above maintenance energy requirements (MERx 1.1-1.2) based on initial BW. Body composition (body fat, lean tissue and bone mineral content) was monitored using dual-energy X-ray absorptiometry. After treatment, dogs that had received dirlotapide for 52 weeks were fed 90% of quantity consumed at week 52. In study A, BW and food intake decreased asymptotically with dose: mean weekly weight loss exceeded 1% at 0.1-0.4 mg/kg. In study B, dirlotapide resulted in significant mean weekly weight loss (>0.8%) and decreased food intake over 24 weeks compared with placebo (P = 0.0001) for all diets. Food restriction minimized post-treatment weight rebound. Dirlotapide administered daily to dogs for up to 52 weeks was clinically safe and resulted in sustained weight reduction.

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)0.007
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 score0.787
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.117
GPT teacher head0.424
Teacher spread0.307 · 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

Citations20
Published2007
Admission routes1
Has abstractyes

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