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Record W2997169481 · doi:10.1123/ijatt.2019-0019

A Comprehensive Nonoperative Rehabilitation Program Including Blood Flow Restriction for a Talus Fracture in a Professional Hockey Player: A Case Report

2019· article· en· W2997169481 on OpenAlexaff
Stephanie Di Lemme, Jon Sanderson, Richard G. Celebrini, Geoffrey Dover

Bibliographic record

VenueInternational Journal of Athletic Therapy & Training · 2019
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of British ColumbiaConcordia University
Fundersnot available
KeywordsBlood flow restrictionRehabilitationMedicinePhysical medicine and rehabilitationPhysical therapyMuscle strengthMuscle atrophyAtrophyResistance trainingPathology

Abstract

fetched live from OpenAlex

A 22-year-old male professional hockey player sustained a nondisplaced talus fracture. We present a comprehensive nonsurgical rehabilitation that includes blood flow restriction (BFR) training. Pain and function measures improved throughout the rehabilitation. Lower limb circumference did not change postinjury. The patient returned to play in less than 7 weeks, while current talar fracture management protocols indicate surgical fixation and 6 weeks of immobilization. BFR training may be useful in injury rehabilitation, negating muscle atrophy and increasing muscle strength while allowing the patient to exercise at relatively low loads. This is the first case of BFR training implemented in early fracture rehabilitation of an athlete.

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)0.002
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 score0.008
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0080.003
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 head0.037
GPT teacher head0.384
Teacher spread0.347 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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