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Record W2606535522 · doi:10.2147/vmrr.s131583

Severe lamotrigine toxicosis in a dog

2017· article· en· W2606535522 on OpenAlexaboutno aff
Danielle Sawyer, Kathryn Gates

Bibliographic record

VenueVeterinary Medicine Research and Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLamotrigineMedicinePsychiatryEpilepsy

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to describe a case of severe lamotrigine toxicosis in a dog, which was successfully treated using minimal medical interventions. CASE SUMMARY: A 7-month-old male, intact, Labrador mix was evaluated because of acute onset of vomiting, rigidity, and dull mentation after ingesting lamotrigine tablets. The estimated oral dose that had been ingested was 278 mg/kg (611.6 mg/lb). Physical examination was unremarkable other than abnormalities noted in the cardiovascular and neurological systems. Neurological examination revealed dull mentation, vertical nystagmus, four-legged extensor limb rigidity, and alligator rolling. Cardiovascular examination revealed pale pink mucous membranes and multifocal ventricular tachycardia. Intravenous (IV) fluids were started at three times maintenance (180 mL/kg/day). Methocarbamol (100 mg/kg [220 mg/lb], rectally) and lidocaine (2 mg/kg [4.4 mg/lb, IV]) were administered. Twenty-four and seventy-two hours after presentation, the dog was clinically normal with no ventricular tachycardia being noted. CONCLUSION: Lamotrigine (6-[2,3-dichlorophenyl]-1,2,4-triazine-3,5-diamine) is an anticonvulsant medication used in humans, which inhibits voltage-gated sodium channels. The clinical success of this case suggests that administration of only methocarbamol for the neurologic effects and lidocaine for the arrhythmias, as well as supportive IV fluid therapy, could be a successful treatment strategy for dogs, even with severe lamotrigine toxicosis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.251
GPT teacher head0.510
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations5
Published2017
Admission routes1
Has abstractyes

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