MétaCan
Menu
Back to cohort
Record W2536484755 · doi:10.1177/1071100716674259

An Anatomic Study of the Percutaneous Endoscopically Assisted Calcaneal Osteotomy Technique to Correct Hindfoot Malalignment

2016· article· en· W2536484755 on OpenAlexaff
Andrea Veljkovic, Joshua N. Tennant, Chamnanni Rungprai, Kaniza Zahra Abbas, Phinit Phisitkul

Bibliographic record

VenueFoot & Ankle International · 2016
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsSt. Paul's HospitalUniversity Health NetworkUniversity of British Columbia
Fundersnot available
KeywordsMedicineCadaveric spasmPercutaneousOsteotomyNeurovascular bundleSurgerySural nerveCadaverCalcaneus

Abstract

fetched live from OpenAlex

BACKGROUND: Open calcaneal osteotomy using traditional methods is associated with complications such as sural nerve injury and potential wound healing problems. We hypothesized that by using novel minimally invasive techniques, these potential risks could be mitigated. This anatomic cadaveric study serves to assess the safety of percutaneous endoscopically assisted calcaneal osteotomy (PECO) compared to a traditional open osteotomy technique. METHODS: Anatomic safety of PECO was assessed using 8 fresh-frozen cadaver below-knee specimens. Lateral calcaneal nerve (LCN) damage was primarily noted and then secondly compared to a potential open surgical incision approach. RESULTS: Only 1 of 11 LCN branches (n = 8 limbs) was transected using PECO, compared to up to 8 of 10 LCN branches (n = 6 limbs) that potentially would have been injured during open surgery. CONCLUSIONS: Percutaneous endoscopically assisted calcaneal osteotomy is a minimally invasive technique that had fewer nerve injuries in this cadaveric model than traditional open surgery. CLINICAL RELEVANCE: Percutaneous endoscopically assisted calcaneal osteotomy due to its less invasive nature may result in fewer neurovascular injuries relative to an open procedure.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.016
GPT teacher head0.295
Teacher spread0.278 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueFoot & Ankle InternationalSame topicFoot and Ankle SurgeryFrench-language works237,207