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Record W2746117548 · doi:10.5435/jaaos-d-15-00680

Revision Total Knee Arthroplasty for the Management of Periprosthetic Fractures

2017· review· en· W2746117548 on OpenAlexaff
Paul R.T. Kuzyk, Evan Watts, David Backstein

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2017
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsSinai Health System
Fundersnot available
KeywordsMedicinePeriprostheticSurgeryImplantArthroplastyPatellaFemurTibiaOrthopedic surgery

Abstract

fetched live from OpenAlex

Periprosthetic fractures after total knee arthroplasty (TKA) can present reconstructive challenges. Not only is the procedure technically complex, but patients with these fractures may have multiple comorbidities, making them prone to postoperative complications. Early mobilization is particularly beneficial in patients with multiple comorbidities. Certain patient factors and fracture types may make revision TKA the ideal management option. Periprosthetic fractures around the knee implant occur most frequently in the distal femur, followed by the tibia and the patella. Risk factors typically are grouped into patient factors (eg, osteoporosis, obesity) and surgical factors (eg, anterior notching, implant malposition). Surgical options for periprosthetic fractures that involve the distal femur or proximal tibia include reconstruction of the bone stock with augments or metal cones or replacement with an endoprosthesis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.050
GPT teacher head0.370
Teacher spread0.321 · 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 designNot applicable
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

Citations57
Published2017
Admission routes1
Has abstractyes

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