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Record W6979893165

Analyse des conséquences du déficit de flexion dorsale de cheville dans les mécanismes de lésions du ligament croisé antérieur

2024· dissertation· en· W6979893165 on OpenAlexaboutno aff

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2024
Typedissertation
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAnkle dorsiflexionAnkleAthletesAnterior cruciate ligamentBiomechanicsRange of motionKnee flexionACL injury
DOInot available

Abstract

fetched live from OpenAlex

Background : ACL injuries are very common, particularly among athletes. On average, amateur athletes suffer between 30 and 162 injuries per 100,000 person-years. ACL injury is a multifactorial pathology, with numerous risk factors, and prevention plays an important role in reducing injuries and the associated costs. The ankle joint is an important link between a horizontal segment (the foot) and a vertical segment (the leg). It must absorb and distribute ground reaction forces throughout the lower limb. Objective : To establish a link between dorsiflexion deficit and ACL injury mechanisms (valgus, increased ground reaction forces). Participants : Active people performing at least three sports sessions per week corresponding to a minimum of 1h of sport per week. Method : Searches were carried out via various databases: PubMed, Science Direct. A total of five articles were selected and analyzed. Inclusion and exclusion criteria were established beforehand. The studies were designed to investigate the relationship between passive dorsiflexion deficit and lower limb biomechanics during functional tasks such as landings and squats (unipodal and bipodal). Dorsiflexion was measured under load. Results : The 5 studies investigated the relationship between dorsiflexion deficit and lower-limb biomechanics. Three studies found a correlation between ankle dorsiflexion deficit and reduced knee flexion, which would result in a weaker landing and poorer stress absorption. Opinions on the other variables differ from author to author. Discussion : The results of these studies need to be weighed up, as they present biases and a low level of evidence. The risk of bias was studied using the Newcastle Ottawa Scale. Despite the correlations found between dorsiflexion and lower-limb biomechanics at risk of ACL injury, no conclusions on any relationship can be drawn. Further studies on this subject are needed to answer the questions posed.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0100.009
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.258
Teacher spread0.249 · 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 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
Published2024
Admission routes1
Has abstractyes

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