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Record W2104171765 · doi:10.1177/230949901302100306

Total Knee Replacement System with a Ceramic Femoral Component versus Two Traditional Metallic Designs: A Prospective Short-Term Study

2013· article· en· W2104171765 on OpenAlexaboutno aff
Philipp Bergschmidt, Rainer Bader, Daniel Kluess, Carmen Zietz, Benjamin Schwemmer, Guenther Kundt, Wolfram Mittelmeier

Bibliographic record

VenueJournal of orthopaedic surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACMedicineOsteoarthritisOxford knee scoreRadiodensityArthroplastySurgeryTotal knee replacementOrthodonticsRadiography

Abstract

fetched live from OpenAlex

PURPOSE: To compare the short-term outcome of the Multigen Plus system using a symmetric ceramic femoral component with that of 2 metallic total knee replacement (TKR) systems. METHODS: 60 patients (62 knees) with osteoarthritis or rheumatoid arthritis underwent primary TKR using the Genia system (n=20), the Multigen Plus system (n=17), and the Multigen Plus system with a ceramic femoral component (n=25). Outcome was evaluated pre- and post-operatively (at 3, 12, and 24 months) using the Hospital for Special Surgery (HSS) score, the Western Ontario and McMaster Universities (WOMAC) score, and the Short-Form 36 (SF-36) score. RESULTS: The 3 groups did not differ significantly at all 4 time points in terms of the HSS score, WOMAC score, and SF-36 score. The range of motion was significantly less in patients treated with the Genia system. Postoperatively, the HSS and WOMAC scores improved significantly in all 3 groups, whereas the SF-36 score improved significantly (at 12 and 24 months) only in patients treated with the Multigen Plus system with a ceramic femoral component. The implant position in most patients was optimal. All radiolucent lines were within 1 mm and did not progress. CONCLUSION: The short-term outcome of the 3 TKR systems was comparable. Ceramic femoral components performed comparably to traditional metallic designs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.276
Teacher spread0.220 · 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 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

Citations16
Published2013
Admission routes1
Has abstractyes

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