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Record W2149850526 · doi:10.1302/0301-620x.94b4.27735

A prospective randomised controlled trial comparing three alternative bearing surfaces in primary total hip replacement

2012· article· en· W2149850526 on OpenAlexaboutno aff
Vasileios S. Nikolaou, Max R. Edwards, Earl R. Bogoch, Emil H. Schemitsch, James P. Waddell

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2012
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisTotal hip replacementRadiological weaponRandomized controlled trialArthroplastySurgeryBearing surfaceDentistryPhysical therapyMaterials science

Abstract

fetched live from OpenAlex

The ideal bearing surface for young patients undergoing total hip replacement (THR) remains controversial. We report the five-year results of a randomised controlled trial comparing the clinical and radiological outcomes of 102 THRs in 91 patients who were < 65 years of age. These patients were randomised to receive a cobalt-chrome on ultra-high-molecular-weight polyethylene, cobalt-chrome on highly cross-linked polyethylene, or a ceramic-on-ceramic bearing. In all, 97 hip replacements in 87 patients were available for review at five years. Two hips had been revised, one for infection and one for peri-prosthetic fracture. At the final follow-up there were no significant differences between the groups for the mean Western Ontario and McMaster Universities osteoarthritis index (pain, p = 0.543; function, p = 0.10; stiffness, p = 0.99), Short Form-12 (physical component, p = 0.878; mental component, p = 0.818) or Harris hip scores (p = 0.22). Radiological outcomes revealed no significant wear in the ceramic group. Comparison of standard and highly cross-linked polyethylene, however, revealed an almost threefold difference in the mean annual linear wear rates (0.151 mm/year versus 0.059 mm/year, respectively) (p < 0.001).

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.122
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.240
Teacher spread0.216 · 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.

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

Citations62
Published2012
Admission routes1
Has abstractyes

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