Treatment and outcome following substantial ketamine overdose in a dog.
Bibliographic record
Abstract
A 9-year-old, 3.7 kg (8.14 lb) neutered male Yorkshire terrier mix was treated following a ketamine overdose after subcutaneous ureteral bypass surgery. Due to an error in communication and misinterpretation of an electronic treatment sheet, the dog was inadvertently placed on a continuous rate infusion (CRI) of ketamine at 67.6 mg/kg per hour, rather than the intended 0.2 mg/kg per hour rate. Four hours after initiation of the ketamine CRI, the dog developed signs indicative of a ketamine overdose including tachycardia, hyperthermia, anisocoria, and hypoglycemia. It was determined the dog had received an iatrogenic overdose of ketamine; the infusion had been running at 67.6 mg/kg per hour, resulting in 270 mg/kg of ketamine over 4 h. Aggressive supportive measures were undertaken, and the dog gradually recovered over an 18-hour period, without lasting consequences of the overdose. To the authors' knowledge, there are no current published reports of a ketamine overdose of this magnitude in a dog. This case report documents an iatrogenic 338 times intravenous ketamine overdose in a dog, which was successfully managed with supportive care. In addition, it highlights the importance of doctor-technician communication and the potential errors in using electronic treatment sheets.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| 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".