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Record W1964661940 · doi:10.1007/s11999-011-1981-0

Risk Factors for Peroneal Nerve Injury and Recovery in Knee Dislocation

2011· article· en· W1964661940 on OpenAlexaff
Christopher Peskun, Jas Chahal, Zvi Y. Steinfeld, Daniel B. Whelan

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2011
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineKnee DislocationOdds ratioCommon peroneal nerveNerve injurySurgeryRetrospective cohort studyOrthopedic surgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Acute knee dislocation is rare but has a high rate of associated neurovascular injuries and potentially limb-threatening complications. These include the substantial morbidity associated with peroneal nerve injury: neuropathic pain, decreased mobility, and considerably reduced function, which not only impairs patient function but complicates treatment. QUESTIONS/PURPOSES: We therefore identified and quantified the risks associated with specific factors for peroneal nerve injury and recovery in patients with knee dislocations. PATIENTS AND METHODS: We retrospectively reviewed the charts of 26 patients, from among a cohort of all 91 knee dislocations, with a peroneal nerve palsy over a 5-year period. We then used univariable and multivariable statistics to identify risk factors predicting peroneal nerve injury and recovery. RESULTS: Gender (odds ratio, 5.47), body mass index (odds ratio, 1.14), and fibular head fracture (odds ratio, 4.77) were associated with peroneal nerve injury. Only younger age was associated with peroneal nerve recovery. CONCLUSIONS: Knowledge of the risk factors for peroneal nerve injury and the predictors of recovery in knee dislocation allows the treating surgeon to have a better understanding of the nature of the neurologic injury and modify management based on the anticipated return of nerve function. LEVEL OF EVIDENCE: Level II, prognostic study. See Guidelines for Authors for a complete description of levels of evidence.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.101
GPT teacher head0.418
Teacher spread0.316 · 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 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

Citations99
Published2011
Admission routes1
Has abstractyes

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