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Record W2764076559 · doi:10.1111/vsu.12726

Limb shortening as a strategy for limb sparing treatment of appendicular osteosarcoma of the distal radius in a dog

2017· article· en· W2764076559 on OpenAlexaboutno aff
Sarah E. Boston, Owen T. Skinner

Bibliographic record

VenueVeterinary Surgery · 2017
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryNeurovascular bundleOsteosarcomaRadiographyOsteotomy

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop and report a novel limb sparing technique for the distal radius in a dog. STUDY DESIGN: Case report. ANIMAL: A 14-year-old, female spayed Labrador Retriever with an osteosarcoma of the right distal radius and a pathological fracture. A previous mast cell tumor had been treated 5 years prior to presentation with marginal excision and a full-course radiation over the right metacarpal bones. The dog had received 2 doses of palliative radiation just prior to presentation. METHODS: A standard resection of the distal radius was used as a strategy to salvage the limb. Instead of replacing the 6-cm bone defect with an endoprosthesis, the limb was acutely shortened and a carpal arthrodesis plate was applied. RESULTS: Postoperative function was good and limb shortening was well-tolerated. Radiographic evidence of early bone healing was noted at the osteotomy site. The dog experienced 3 postoperative complications: a focal area of skin necrosis managed successfully via surgical revision; infection resolving after long-term antibiotherapy; and a fracture of the third metacarpal bone through a screw hole, managed via screw removal and a custom external prosthesis. The patient was euthanatized due to presumptive chemotherapy complications 127 days after the procedure. CONCLUSION: Limb shortening limb salvage is technically feasible and can result in excellent limb use postoperatively, in spite of a significant loss in limb length.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.175
GPT teacher head0.370
Teacher spread0.195 · 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 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

Citations20
Published2017
Admission routes1
Has abstractyes

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