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Record W2261629282 · doi:10.1302/0301-620x.93b4.26149

Comparison of total hip replacement with and without cement in patients younger than 50 years of age

2011· article· en· W2261629282 on OpenAlexaboutno aff
Y.-H. Kim, J.-S. Kim, Jang-Won Park, Jong-Hwan Joo

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2011
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteolysisHarris Hip ScoreWOMACOsteoarthritisSurgeryTotal hip arthroplastyRadiographyIncidence (geometry)AcetabulumArthroplasty

Abstract

fetched live from OpenAlex

There have been comparatively few studies of the incidence of osteolysis and the survival of hybrid and cementless total hip replacements (THRs) in patients younger than 50 years of age. We prospectively reviewed 78 patients (109 hips) with a hybrid THR having a mean age of 43.4 years (21 to 50) and 79 patients (110 hips) with a cementless THR with a mean age of 46.8 years (21 to 49). The patients were evaluated clinically using the Harris hip score, the Western Ontario and McMaster Universities (WOMAC) osteoarthritis score and the University of California, Los Angeles (UCLA) activity score. Radiographs and CT scans were assessed for loosening and osteolysis. The mean follow-up was for 18.4 years (16 to 19) in both groups. The mean post-operative Harris hip scores (91 points versus 90 points), the mean WOMAC scores (11 points versus 13 points) and UCLA activity scores (6.9 points versus 7.1 points) were similar in both groups. The revision rates of the acetabular component (13% versus 16%) and the femoral component (3% versus 4%), and the survival of the acetabular component (87% versus 84%) and the femoral component (97% versus 96%) were similar in both groups. Although the long-term fixation of the acetabular metallic shell and the cemented and cementless femoral components was outstanding, wear and peri-acetabular osteolysis constitute the major challenges of THR in young patients.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.030
GPT teacher head0.243
Teacher spread0.213 · 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

Citations61
Published2011
Admission routes1
Has abstractyes

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