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Record W1579132866

An evaluation of the analgesic effects of meloxicam in addition to epidural morphine/mepivacaine in dogs undergoing cranial cruciate ligament repair.

2003· article· en· W1579132866 on OpenAlexaff
David Fowler, Kevin Isakow, Nigel Caulkett, Cheryl Waldner

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMeloxicamMedicineMepivacaineAnesthesiaMorphineAnalgesicEpidural administrationVisual analogue scaleCruciate ligamentSurgeryAnterior cruciate ligamentBupivacaine
DOInot available

Abstract

fetched live from OpenAlex

The analgesic efficacy of an epidural morphine/mepivacaine combination alone versus epidural morphine/mepivacaine in combination with meloxicam administered prior to the onset of anesthesia was assessed in 20 dogs undergoing cranial cruciate ligament repair. Numerical and visual analog pain scores were performed prior to anesthesia and at 6, 8, 12, 16, and 24 hours after epidural administration by a trained observer, blinded to treatment. An analgesiometer was used to determine the amount of pressure required to produce an avoidance response at the incision site. Animals that received meloxicam demonstrated a trend toward decreased pain scores over all time periods. Visual analog pain scores tended to be lower in dogs receiving meloxicam across all time periods, with a significant interaction between time and visual analog score at 6 and 8 hours (P < 0.05). No dogs receiving meloxicam required rescue analgesia, while 3 of 10 dogs in the epidural only group required rescue analgesia. Administration of meloxicam in addition to epidural morphine plus mepivacaine conveys improved analgesia as compared with epidural alone. Postoperative analgesia is reliably maintained for 24 hours following administration.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.263
Teacher spread0.240 · 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 designObservational
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

Citations27
Published2003
Admission routes1
Has abstractyes

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