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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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.422

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)0.0000.000

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 head0.018
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 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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