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Record W2274783442 · doi:10.1302/0301-620x.95b11.31604

Metal-on-metal hip resurfacing compared with 28-mm diameter metal-on-metal total hip replacement

2013· article· en· W2274783442 on OpenAlexaffabout
Pascal‐André Vendittoli, Charles Rivière, Alain Roy, Janie Barry, Daniel Lusignan, Martin Lavigne

Bibliographic record

VenueThe Bone & Joint Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsMedicineHip resurfacingOsteoarthritisOsteolysisSurgeryFemoral headTotal hip replacementTotal hip arthroplasty

Abstract

fetched live from OpenAlex

A total of 219 hips in 192 patients aged between 18 and 65 years were randomised to 28-mm metal-on-metal uncemented total hip replacements (THRs, 107 hips) or hybrid hip resurfacing (HR, 112 hips). At a mean follow-up of eight years (6.6 to 9.3) there was no significant difference between the THR and HR groups regarding rate of revision (4.0% (4 of 99) vs 5.8% (6 of 104), p = 0.569) or re-operation rates without revision (5.1% (5 of 99) vs 2.9% (3 of 104), p = 0.428). In the THR group one recurrent dislocation, two late deep infections and one peri-prosthetic fracture required revision, whereas in the HR group five patients underwent revision for femoral head loosening and one for adverse reaction to metal debris. The mean University of California, Los Angeles activity scores were significantly higher in HR (7.5 (sd 1.7) vs 6.9 (sd 1.7), p = 0.035), but similar mean Western Ontario and McMaster Universities Osteoarthritis Index scores were obtained (5.8 (sd 9.5) in HR vs 5.1 (sd 8.9) in THR, p = 0.615) at the last follow-up. Osteolysis was found in 30 of 81 THR patients (37.4%), mostly in the proximal femur, compared with two of 83 HR patients (2.4%) (p < 0.001). At five years the mean metal ion levels were < 2.5 μg/l for cobalt and chromium in both groups; only titanium was significantly higher in the HR group (p = 0.001). Although revision rates and functional scores were similar in both groups at mid-term, long-term survival analysis is necessary to determine whether one procedure is more advantageous than the other.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.252
Teacher spread0.222 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations41
Published2013
Admission routes2
Has abstractyes

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