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Tilt Table Recovery of Horses After Orthopedic Surgery: Fifty‐Four Cases (1994–2005)

2007· article· en· W2059510563 on OpenAlexaff
Colette Remziye Elmas, Antonio M. Cruz, Carolyn L. Kerr

Bibliographic record

VenueVeterinary Surgery · 2007
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineOrthopedic surgerySurgeryAnestheticAnesthesiaInternal fixationMedical record

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe an assisted anesthetic recovery technique using a tilt table for horses after high-risk orthopedic-related procedures and to evaluate outcome. STUDY DESIGN: Retrospective study. SAMPLE POPULATION: Anesthetic recoveries (n=54) for 36 horses. METHODS: Medical records (April 1994-October 2005) for horses that had high-risk orthopedic surgery and recovery from general anesthesia on a tilt table were reviewed. Information about the surgical procedure, anesthetic and recovery period was analyzed. RESULTS: Of 54 anesthetic recoveries, 1 horse (1.9%) had complete failure of internal fixation during recovery and was euthanatized. Six (11% recoveries) horses failed to adapt to the tilt table system, which necessitated transfer to a conventional recovery room. Complications without important consequences for clinical outcome (skin abrasions, myositis, cast breakage, partial implant failure) occurred during 8 (15%) recoveries. CONCLUSIONS: A tilt table recovery system was associated with minimal incidence of serious complications. Potential disadvantages of the system are the number of personnel required, longer recovery time, and the need for a specialized table. CLINICAL RELEVANCE: A tilt table is a useful system for recovering horses believed to be at increased risk of injury during anesthetic recovery after high-risk orthopedic-related procedures.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.102
GPT teacher head0.326
Teacher spread0.224 · 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.

Study designNot applicable
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

Citations22
Published2007
Admission routes1
Has abstractyes

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