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Record W2346915143 · doi:10.1302/0301-620x.98b5.35969

Revision surgery for the stiff total knee arthroplasty

2016· article· en· W2346915143 on OpenAlexaffabout
James Donaldson, Francois Tudor, Jeffrey D. Gollish

Bibliographic record

VenueThe Bone & Joint Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisSurgeryRange of motionContractureTotal knee arthroplastyArthroplastyRehabilitationPhysical therapy

Abstract

fetched live from OpenAlex

AIMS: The aim of this study was to examine the results of revision total knee arthroplasty (TKA) undertaken for stiffness in the absence of sepsis or loosening. PATIENTS AND METHODS: We present the results of revision surgery for stiff TKA in 48 cases (35 (72.9%) women and 13 (27.1%) men). The mean age at revision surgery was 65.5 years (42 to 83). All surgeries were performed by a single surgeon. Stiffness was defined as an arc of flexion of < 70° or a flexion contracture of > 15°. The changes in the range of movement (ROM) and the Western Ontario and McMasters Osteoarthritis index scores (WOMAC) were recorded. RESULTS: At a mean follow up of 59.9 months (12 to 272) there was a mean improvement in arc of movement of 45.0°. Mean flexion improved from 54.4° (5° to 100°) to 90° (10° to 125°) (p < 0.05) and the mean flexion contracture decreased from 12.0° (0° to 45°) to 3.5° (0° to 25°) (p < 0.05). The mean WOMAC scores improved for pain, stiffness and function. In patients with extreme stiffness we describe a novel technique, which we have called the 'sloppy' revision. This entails downsizing the polyethylene insert by 4 mm and using a more constrained liner to retain stability. CONCLUSION: To our knowledge, this is the largest series of revision surgeries for stiffness reported in the literature where infection and loosening have been excluded. TAKE HOME MESSAGE: Whilst revision surgery is technically demanding, improvements in ROM and outcome can be achieved, particularly when the revision is within two years of the primary surgery. Cite this article: Bone Joint J 2016;98-B:622-7.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
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 head0.031
GPT teacher head0.265
Teacher spread0.233 · 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

Citations50
Published2016
Admission routes2
Has abstractyes

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