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Record W2754464480 · doi:10.1177/1098612x17730173

Analgesic effects of gabapentin and buprenorphine in cats undergoing ovariohysterectomy using two pain-scoring systems: a randomized clinical trial

2017· article· en· W2754464480 on OpenAlexaff
Paulo V. Steagall, Javier Benito, Beatriz P. Monteiro, Graeme M. Doodnaught, Guy Beauchamp, Marina C. Evangelista

Bibliographic record

VenueJournal of Feline Medicine and Surgery · 2017
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBuprenorphineMedicineAnesthesiaGabapentinMeloxicamPlaceboAnalgesicRandomized controlled trialOpioidSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Objectives The aim of the study was to evaluate the analgesic efficacy of gabapentin-buprenorphine in comparison with meloxicam-buprenorphine or buprenorphine alone, and the correlation between two pain-scoring systems in cats. Methods Fifty-two adult cats were included in a randomized, controlled, blinded study. Anesthetic protocol included acepromazine-buprenorphine-propofol-isoflurane. The gabapentin-buprenorphine group (GBG, n = 19) received gabapentin capsules (50 mg PO) and buprenorphine (0.02 mg/kg IM). The meloxicam-buprenorphine group (MBG, n = 15) received meloxicam (0.2 mg/kg SC), buprenorphine and placebo capsules (PO). The buprenorphine group (BG, n = 18) received buprenorphine and placebo capsules (PO). Gabapentin (GBG) and placebo (MBG and BG) capsules were administered 12 h and 1 h before surgery. Postoperative pain was evaluated up to 8 h after ovariohysterectomy using a multidimensional composite pain scale (MCPS) and the Glasgow pain scale (rCMPS-F). A dynamic interactive visual analog scale (DIVAS) was used to evaluate sedation. Rescue analgesia included buprenorphine and/or meloxicam if the MCPS ⩾6. A repeated measures linear model was used for statistical analysis ( P <0.05). Spearman's rank correlation between the MCPS and rCMPS-F was evaluated. Results The prevalence of rescue analgesia with a MCPS was not different ( P = 0.08; GBG, n = 5 [26%]; MBG, n = 2 [13%]; BG, n = 9 [50%]), but it would have been significantly higher in the BG (n = 14 [78%]) than GBG ( P = 0.003; n = 5 [26%]) and MBG ( P = 0.005; n = 4 [27%]) if intervention was based on the rCMPS-F. DIVAS and MCPS/rCMPS-F scores were not different among treatments. A strong correlation was observed between scoring systems ( P <0.0001). Conclusions and relevance Analgesia was not significantly different among treatments using an MCPS. Despite a strong correlation between scoring systems, GBG/MBG would have been superior to the BG with the rCMPS-F demonstrating a potential type II error with an MCPS due to small sample size.

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.172
GPT teacher head0.434
Teacher spread0.262 · 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 designRandomized trial
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

Citations59
Published2017
Admission routes1
Has abstractyes

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