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Record W4410536364 · doi:10.7759/cureus.84483

Chronic Exertional Compartment Syndrome of Bilateral Lower Limbs and Forearms in an Elite Ice Hockey Athlete: A Case Report

2025· article· en· W4410536364 on OpenAlexaff
Kevin Zhao, Peter Staunton, Simon Martel, Louis‐Nicolas Veilleux, Drew Schupbach, Thierry Pauyo

Bibliographic record

VenueCureus · 2025
Typearticle
Languageen
FieldMedicine
TopicMuscle and Compartmental Disorders
Canadian institutionsShriners Hospitals for Children - CanadaMcGill University
Fundersnot available
KeywordsMedicineIce hockeyCompartment (ship)Physical therapyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Chronic exertional compartment syndrome (CECS) involves increased intracompartmental pressures (ICPs) induced by physical activity, leading to intense pain and associated neurological symptoms that resolve with rest. Classically, it is associated with young male athletes. The lower limbs are typically affected in running athletes and marching military members, while the upper limbs are generally involved in motorcyclists and rowers. Conservative treatment options involve activity modification, such as alteration of foot strike patterns and botulinum injections, while surgical treatments range from open to percutaneous fasciotomy. CECS is rare and remains a challenging diagnosis. In addition to history and physical exam, magnetic resonance imaging and intracompartmental measurements throughout exercise stress tests are described. In this article, we outline the first reported case of CECS in an ice hockey athlete involving all four limbs that was successfully diagnosed with a continuous ICP monitor and treated with open fasciotomy of all four limbs.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.306
Teacher spread0.287 · 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 designCase report
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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