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Removal of Solidly Fixed Implants During Revision Hip and Knee Arthroplasty

2005· review· en· W2170838855 on OpenAlexaff
Bassam A. Masri, Philip A. Mitchell, Clivе P. Duncan

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2005
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineArthroplastyImplantSurgeryOrthodontics

Abstract

fetched live from OpenAlex

The removal of solidly fixed implants during revision hip and knee arthroplasty is a technically challenging procedure with the potential for a large amount of bone loss during component removal. This bone loss may compromise the subsequent reconstruction. Careful preoperative planning is essential before undertaking removal of solidly fixed implants. The surgeon should determine the type and size of the implants and be familiar with any specialized removal equipment that may be available. For both the hip and knee, extensive exposure is often necessary. Removal of a well-fixed femoral component often requires an extended trochanteric osteotomy. The most difficult component to remove from the knee is a well-fixed cementless patellar component. The primary goal in removing well-fixed components is to minimize loss of surrounding bone, which requires effective planning and often access to specialized tools and techniques.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.033
GPT teacher head0.330
Teacher spread0.297 · 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

Citations81
Published2005
Admission routes1
Has abstractyes

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