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Advances in Diagnosis and Management of Lateral Ankle Instability: A Review of Current Literature

2023· review· en· W4390277669 on OpenAlexaff
Amiethab A. Aiyer, Sudarsan Murali, Anish R. Kadakia

Bibliographic record

VenueJAAOS Global Research and Reviews · 2023
Typereview
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsWeyerhauser (Canada)
Fundersnot available
KeywordsAnkleMedicineSyndesmosisPhysical medicine and rehabilitationAnkle sprainArthroscopyPhysical therapySurgeryFibulaTibia

Abstract

fetched live from OpenAlex

Lateral ankle sprains and instability are an increasingly identified pain point for patients, accounting for 20 to 25% of musculoskeletal injuries. Lateral ankle injuries are especially concerning given the propensity for patients to develop chronic lateral ankle instability and for the high risk of reinjury on an unstable ankle. With the complex articulation of the tibiofibular syndesmosis, subtalar, and talocrural joints, pinpointing ankle dysfunction remains difficult. Multiple reviews have evaluated management and diagnosis of lateral ankle instability, but with newer treatment options available, a more comprehensive assessment of the current literature was conducted. Although multiple surgical options exist, many nonsurgical functional options have also been developed for patients that may help patients prevent the development of chronic lateral ankle instability. In recent times, many new options have come up, including in-office needle arthroscopy and continual advancements in diagnosis and our understanding of this difficult topic. Multiple reviews have evaluated the management and diagnosis of lateral ankle instability, but with newer treatment options available, a more comprehensive assessment of the current literature was conducted. Given this, this review will help to highlight new diagnostic and nonsurgical therapeutic options for the management of lateral ankle instability.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.527
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.262
GPT teacher head0.529
Teacher spread0.267 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations15
Published2023
Admission routes1
Has abstractyes

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