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Record W4412362998 · doi:10.12775/qs.2025.43.62354

Ankle Sprains: Clinical Practice and Guideline-Based Treatment Strategies

2025· article· en· W4412362998 on OpenAlexaboutno aff
Maciej Pachana, Piotr Kukuła, Maciej Ziomek, Marcin Piersiak, Hubert Sawczuk, Anna Tomasiewicz, Jan Zabierowski, Julia Marschollek

Bibliographic record

VenueQuality in Sport · 2025
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsGuidelineAnkleClinical PracticeMedicinePhysical therapyPhysical medicine and rehabilitationSurgeryPathology

Abstract

fetched live from OpenAlex

Ankle sprains, particularly lateral sprains involving the anterior talofibular ligament (ATFL), represent up to 85% of ankle injuries and are common in both athletic and general populations. Despite their prevalence, misdiagnosis and inadequate treatment can lead to chronic ankle instability and post-traumatic osteoarthritis. This narrative review synthesizes current clinical guidelines and evidence-based practices for diagnosis and treatment. Clinical assessment, supported by the Ottawa Ankle Rules, ultrasound, and MRI, enables accurate injury classification. Conservative treatment is preferred for Grade I and II injuries, with early mobilization and functional support—especially within the POLICE protocol—demonstrating superior outcomes. Exercise therapy effectively reduces recurrence, while surgical intervention is reserved for Grade III injuries or chronic instability in high-demand patients. Timely and structured rehabilitation remains key to restoring ankle function.

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)0.012
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.002

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 head0.090
GPT teacher head0.490
Teacher spread0.400 · 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 designNot applicable
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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