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Record W7027562738

Clinical Assessment after Periprosthetic Distal Femur Fracture Repair with Weight-Bearing CT

2025· article· en· W7027562738 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPeriprostheticInternal fixationRadiographyReduction (mathematics)ArthroplastyFemurComputed tomographyFixation (population genetics)
DOInot available

Abstract

fetched live from OpenAlex

IPeriprosthetic distal femur fractures (PDFFs) following total knee arthroplasty (TKA) pose a growing challenge due to rising TKA rates and aging populations. This thesis examines the efficacy of open reduction and internal fixation (ORIF) with locking plates in 16 patients at Western University's London Health Sciences Centre, Canada. It utilizes Su and Rorabeck-Taylor classification systems and weight-bearing computed tomography (WBCT) to evaluate outcomes. All patients achieved radiographic union at one year without complications, yet patient-reported outcomes (KOOS Pain: 62.1, ADL: 47.9, KSS: 37.1, UCLA: 3.7) revealed moderate functional recovery with persistent limitations, showing no correlation with fracture type or screw placement. WBCT enhanced stability assessment. While ORIF ensures bone healing, the findings highlight the need for improved rehabilitation strategies. This study informs PDFF management, significant given Canada's projected $13 billion TKA burden by 2030.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.040
GPT teacher head0.346
Teacher spread0.306 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

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