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Record W3010876398 · doi:10.1177/1938640020910953

Arthroscopic Repair of Talar Osteochondral Defects With Umbilical Cord Allograft: A Prospective, Single-Center, Pilot Study

2020· article· en· W3010876398 on OpenAlexaff
Murray J. Penner, Alastair Younger, Kevin Wing, Mark Cresswell, Andrea Veljkovic

Bibliographic record

VenueFoot & Ankle Specialist · 2020
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineProspective cohort studySurgeryAnkleVisual analogue scaleOsteoarthritisUmbilical cordSingle Center

Abstract

fetched live from OpenAlex

Cryopreserved umbilical cord (UC) allografts have been shown to promote postoperative wound healing by suppressing inflammation and reducing scar formation. The purpose of this study was to determine whether adjunctive use of UC may improve clinical and functional outcomes following arthroscopic repair of talar osteochondral defects (OCDs). A total of 10 patients with talar OCDs that failed nonoperative treatment were enrolled in this single-center, prospective, pilot study. Clinical and functional outcomes were assessed using the Ankle Osteoarthritis Scale (AOS), Foot and Ankle Ability Measure, and Visual Analog Scale (VAS) pain scale at 6, 12, 24, and 52 weeks postoperatively. Results showed a consistent improvement in all outcome measures. VAS pain scores significantly improved from 4.2 ± 2.9 to 1.3 ± 2.2 at 52 weeks (P = .015). AOS difficulty and pain scores nonsignificantly improved from 27.0 ± 24.6 and 33.1 ± 28.3 at baseline to 15.3 ± 20.5 and 14.8 ± 18.7 at 52 weeks, respectively. The clinical outcome improvement was accompanied by significant reduction in OCD defect size and associated bone marrow lesion. This pilot study suggests that adjunctive use of UC during arthroscopic repair of talar OCD may lead to clinical and functional improvement. Levels of Evidence: Level II: Prospective Cohort Study

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 score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.046
GPT teacher head0.268
Teacher spread0.222 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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