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Record W4412488619

Dexmedetomidine constant-rate infusion with additional partial intravenous anesthesia for a dog undergoing partial pancreatectomy for an insulinoma.

2025· article· en· W4412488619 on OpenAlexaffabout
Tainor Tisotti

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsInsulinomaDexmedetomidineAnesthesiaMedicinePancreatectomyPancreasInternal medicineSedation
DOInot available

Abstract

fetched live from OpenAlex

Alpha-2 adrenergic agonist use in the anesthetic management of dogs undergoing partial pancreatectomy has been reported, but only as single-bolus administration of medetomidine in the premedication or low-dose constant-rate infusion (CRI) of dexmedetomidine, without other systemic analgesic drugs. A 10-year-old Boston terrier diagnosed with an insulinoma was presented to the Ontario Veterinary College Health Sciences Centre (Guelph, Ontario). The anesthetic management for partial pancreatectomy included a high-dose dexmedetomidine CRI (4 μg/kg per hour) as well as lidocaine and fentanyl CRIs for additional analgesia and minimum alveolar concentration reduction. A low-dose norepinephrine CRI was used to maintain blood pressure and improve cardiac output. Overall, blood glucose concentration was controlled, no adverse effects were detected, and the dog did not develop pancreatitis postoperatively. Anesthetic management with a high-dose dexmedetomidine CRI along with other systemic analgesia has apparently not been reported for dogs presented for partial pancreatectomy due to insulinoma. Key clinical message: A high-dose dexmedetomidine CRI along with other systemic analgesia was successfully used to manage a dog undergoing partial pancreatectomy for an insulinoma.

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)0.000
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.261
Teacher spread0.233 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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