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Record W2116361060

Knee dislocations: experience at the Hôpital du Sacré-Coeur de Montréal.

2004· article· en· W2116361060 on OpenAlexaffabout
Max Talbot, Greg Berry, Julio Fernandes, Pierre Ranger

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Range of motionPosterior cruciate ligamentSurgeryCruciate ligamentAnterior cruciate ligament
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Although many options exist for ligament reconstruction in knee dislocations, the optimal treatment remains controversial. Allografts and autografts have both been used to reconstruct the cruciate ligaments. We present the results of reconstruction using artificial ligaments at Hôpital du Sacré-Coeur in Montréal. METHODS: We reviewed the treatment of all patients with knee dislocations seen between June 1996 and October 1999. The Lysholm score, ACL-quality of life (QoL) questionnaire, physical examination and Telos instrumented laxity measurement were used to evaluate the results. RESULTS: Twenty patients (21 knees) participated in the study. The mean (and standard deviation [SD]) Lysholm score was 71.7 (18). Results from the ACL-QoL questionnaire showed a global impairment in QoL. Mean (and SD) range of motion and flexion were 118 degrees (10.9 degrees) and 2 degrees (2.9 degrees) respectively. Mean (and SD) radiologic laxity evaluated with Telos for the anterior and posterior cruciate ligaments were 6.1 (5.7) mm and 7.3 (4.5) mm respectively. CONCLUSIONS: Knee reconstruction with artificial ligaments shows promise, but further studies are necessary before it can be recommended for widespread use. This is the first study to show specifically a severe impairment in QoL in this patient population.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.218

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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 designOther design
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

Citations48
Published2004
Admission routes2
Has abstractyes

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