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Record W7117112788 · doi:10.1177/2473011425s00484

Thickness of the Extensor Retinaculum and Crural Fascia of the Ankle: Zone Specific Cadaveric Analysis to Optimize Surgical Repair Following an Anterior Approach to the Ankle

2025· article· en· W7117112788 on OpenAlexaboutno aff
Xiuming Shi, Abdullah Zein, Jacob Matz, William Mayer, Erin Bigney, Rattina Dasse Nadaradjan, Oreoluwa Alugo, Rory McPhee, Hirbod Abootalebi

Bibliographic record

VenueFoot & Ankle Orthopaedics · 2025
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsCadaveric spasmRetinaculumCadaverAnkleFasciaTendonDeep fascia

Abstract

fetched live from OpenAlex

Research Type: Level 4 – Case series Introduction/Purpose: Total ankle arthroplasty (TAA) through an anterior approach is a widely performed procedure. The success of this procedure can be substantially compromised by wound healing complications. The multiple extensor tendons on the anterior aspect of the ankle are covered by the extensor retinaculum and the crural fascia, creating an effective restraint and preventing tendon bowstringing. Repairing this layer following an anterior approach to the ankle reduces tension on the skin and may prevent wound healing complications. Details regarding the shape and thickness of the extensor retinaculum and crural fascia remain underexplored. The purpose of this cadaveric investigation is to identify the zones of maximal tissue thickness. This knowledge may optimize the surgeons’ ability to repair this important layer. Methods: The study used ten cadaver lower limb specimens from the Dalhousie Body Donation Program. The study was approved by the Local Ethics Board. An anterior incision of 15cm was made to reveal the area of interest, followed by the gross analysis of the shape of the IER. Histological samples were extracted using a 4mm punch biopsy, with 12 samples per specimen in four rows spaced 3 cm apart. Each row contained samples over the extensor hallucis longus (EHL), extensor digitorum longus (EDL), tibialis anterior (TA), for a total of 120 specimens. Samples were fixed in 10% formalin, sectioned, and mounted on slides for analysis. ImageJ was used to assess the thickness in um. SPSS was used to analyze the data by averaging five measurements per sample, then averaging these values across all ten specimens for each zone and calculating the standard deviation. An ANOVA was performed to compare the averages. Results: Of the ten specimens, only one had the X-shaped IER, the rest were Y-shaped. The thickest portions of the extensor retinaculum were at the level of the ankle joint (zone 8: 641.47±322.00 and 9: 632.67 ±350.65) and 3 cm from the ankle joint (zone 4: 621.49 ± 306.90). On average, qualitatively, the extensor retinaculum tissue overlying the TA and EHL was the thickest. However, One-way ANOVAs showed no significant differences in thickness between horizontally grouped (F = 1.121, p = .353), vertically grouped (F = .348, p = .709), or individual zones (F = .669, p = .765). Conclusion: Quantitatively, the result of the study showed no variability, as there was no consistent thickness variation across zones when using one-way ANOVA comparing horizontal and vertical grouping as well as individual zones. However, qualitatively, zones 4, 8, and 9 appeared thicker. In conclusion, there is no one region where surgical reinforcement may improve surgical wound healing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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