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Record W3214079380 · doi:10.1002/9781119413936.ch39

Patellar Resurfacing in Total Knee Arthroplasty

2021· other· en· W3214079380 on OpenAlexaff
Michael G. Zywiel, Rajiv Gandhi, Nizar N. Mahomed

Bibliographic record

VenueEvidence-Based Orthopedics · 2021
Typeother
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineOsteoarthritisPatellaTotal knee replacementArthroplastyAnterior knee painSurgeryKnee replacementTotal knee arthroplastyQuality of life (healthcare)Knee painAlternative medicine

Abstract

fetched live from OpenAlex

This chapter presents a case scenario of a 67-year-old woman with end-stage tricompartmental osteoarthritis of the knee, and who is otherwise independent, undergoes elective total knee replacement. Some knee surgeons advocate leaving the native patellar surface intact, others recommend routine resurfacing with a polyethylene component, while yet others recommend selective resurfacing based on one or more patient factors and/or intraoperative findings. The primary goals of total knee replacement surgery are to improve patients’ quality of life on an elective basis, specifically in terms of reducing pain and functional limitations associated with degenerative disease of the Knee. Many patients with symptomatic osteoarthritis are otherwise healthy and independent in their community. The need to undergo reoperation following primary knee replacement surgery is an undesirable outcome for all involved. Patellar resurfacing is associated with lower reoperation rates following total knee arthroplasty, particularly for patella-related indications. The chapter provides recommendations for implementing evidence-based practice in the clinical setting.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.037
GPT teacher head0.289
Teacher spread0.252 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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