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Record W4411456306 · doi:10.3390/vetsci12060599

Development of a Pericapsular Knee Desensitization Technique in Dogs: An Anatomical Cadaveric Study

2025· article· en· W4411456306 on OpenAlexaff
Marta Garbin, Raiane A. Moura, Yasmim C. Souza, Mariana Braga Cavalcanti, Adam W. Stern, Marta Romano, Enzo Vettorato, Pablo E. Otero, Diego A. Portela

Bibliographic record

VenueVeterinary Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineCadaveric spasmCadaverUltrasoundDissection (medical)Gross anatomyAnatomyRadiology

Abstract

fetched live from OpenAlex

Regional anesthesia techniques targeting articular nerve branches offer promising avenues for managing articular pain. This study developed and compared the success rates of an ultrasound-guided versus a blind pericapsular knee desensitization (PKD) technique in canine cadavers. In Phase I, gross dissection and ultrasound evaluations were performed in eight limbs to characterize the anatomy of the medial (MAN), lateral (LAN), and posterior (PAN) articular branches of the saphenous, common fibular, and tibial nerves, respectively, and to identify suitable anatomical and ultrasonographic landmarks. In Phase II, ultrasound-guided and blind PKD injections of a dye solution were randomly performed in 10 cadavers (20 limbs), followed by dissection and histological assessment of staining accuracy. The ultrasound-guided technique achieved a significantly higher overall success rate (96.7%) than the blind technique (73.3%; p = 0.02). The MAN was successfully stained in 100% of ultrasound-guided and 50% of blind injections (p = 0.03), while the LAN and PAN were stained with high but comparable success. Parent nerve involvement was minimal for MAN and PAN but frequent for the common fibular nerve following LAN injections. Histological confirmation supported the anatomical findings, although PAN identification remained inconsistent. These results support the feasibility and increased precision of ultrasound-guided PKD, providing a foundation for further clinical evaluation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.037
GPT teacher head0.350
Teacher spread0.313 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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