Intravenous lipid emulsion therapy in three cases of canine naproxen overdose
Bibliographic record
Abstract
OBJECTIVE: To report a case series of canine naproxen overdoses successfully treated with intravenous lipid emulsion therapy (IVLE). SERIES SUMMARY: Three dogs were presented for acute ingestion of naproxen and were treated with IVLE. Baseline and post treatment serum naproxen concentrations were measured. The first exposure involved ingestion of 61 mg/kg of an over-the-counter naproxen formulation in a 7-month-old male intact Labrador Retriever. Pre-IVLE toxin concentration assessed by high performance liquid chromatography (HPLC) was 73 μg/mL with a one-hour post-IVLE concentration decreasing to 30 μg/mL. The second and third exposures were 3-year-old female spayed Pembroke Welsh Corgi dogs from the same family, presented for potential ingestion of up to 207 mg/kg of a prescription strength naproxen formulation. Pre-IVLE naproxen concentration by HPLC for case 2 was 30 μg/mL with a reduction to 12 μg/mL and 7.2 μg/mL 1 and 3 hours post-IVLE treatment, respectively. For case 3, pre-IVLE naproxen concentration by HPLC was 86 μg/mL with post concentrations at 21 μg/mL one hour and 10 μg/mL 3 hours post-IVLE administration. NEW OR UNIQUE INFORMATION PROVIDED: Naproxen is a nonsteroidal anti-inflammatory drug with a long half-life and narrow margin of safety in dogs. Ingestion of > 5 mg/kg has been associated with adverse gastrointestinal effects, including ulceration. At doses > 10-25 mg/kg, acute kidney failure has been reported, and at doses > 50 mg/kg, neurologic abnormalities occur. This is the first reported use of IVLE for treatment of naproxen overdose with documented decrease in serum toxin concentrations shortly after administration. No long-standing gastrointestinal, renal, or neurologic effects occurred in these dogs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".