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A Pitfall on Postoperative Radiographs in Dogs After Tibial Plateau Leveling Osteotomy

2014· article· en· W2138927908 on OpenAlexaff
Julien Olive, Mélaine Thiery, Nadège Chailleux, Laurent Blond

Bibliographic record

VenueVeterinary Surgery · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineRadiodensityRadiographyOsteotomyTibiaCruciate ligamentDiaphysisOrthodonticsOrthopedic surgerySurgeryAnterior cruciate ligament

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify the cause of an occasional radiolucent line in the tibia on postoperative radiographs after tibial plateau leveling osteotomy (TPLO) in dogs. STUDY DESIGN: Retrospective case series and ex vivo experiment. SAMPLE POPULATION: Dogs (n = 80; 87 stifles) with cranial cruciate ligament (CCL) rupture that had TPLO; and 4 canine tibia specimens. METHODS: Medical records (2007-2010) and radiographs of dogs that had TPLO were reviewed and examined for presence of a radiolucent line on postoperative radiographs. The TPLO procedure was reproduced ex vivo to determine the origin of this line by use of metallic wires to identify bone contours. RESULTS: A curvilinear radiolucent line was visible in 14 (16%) tibias and was 5.4 times more likely to be visible with lateral misalignment of the tibial diaphysis relative to the plateau and 2.6 times more likely visible on caudocranial radiographs with the stifle in outward rotation. Fracture complication rate was higher in dogs with this radiolucent line (P = .02) and with lateral misalignment of the tibial diaphysis relative to the plateau (risk ratio, 3.8). The line could be reproduced ex vivo and caused by superimposition of the craniomedial border of osteotomy with the tibial plateau. CONCLUSIONS: The radiolucent line was a spurious fracture line created by the medial margin of the tibial osteotomy and confounding factors such as tibial misalignment may explain the apparently associated higher complication rate.

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)0.001
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 score0.274
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.063
GPT teacher head0.297
Teacher spread0.234 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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