MétaCan
Menu
Back to cohort
Record W4312769817 · doi:10.5371/hp.2022.34.4.211

Results of Hip Arthroplasty Using a COREN Stem at a Minimum of Ten Years

2022· article· en· W4312769817 on OpenAlexaboutno aff
Joon Soon Kang, Yoon Cheol Nam, Dae Gyu Kwon, Dong Jin Ryu

Bibliographic record

VenueHip & Pelvis · 2022
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
FundersInha University
KeywordsMedicinePeriprostheticHarris Hip ScoreSurgeryImplantOsteolysisTotal hip arthroplastyArthroplastyFemur

Abstract

fetched live from OpenAlex

Purpose: We report on the 10-year clinical hip function and radiologic outcomes of patients who underwent hip arthroplasty using a COREN stem. Materials and Methods: A consecutive series of 224 primary cementless hip arthroplasty implantations were performed using a COREN stem between 2009 and 2011; among these, evaluation of 128 hips was performed during a minimum follow-up period of 10 years. The mean age of patients was 65.4 years (range, 40-82 years) and the mean duration of follow-up was 10.8 years (range, 10-12 years). Evaluation of clinical hip function and radiologic implant outcomes was performed according to clinical score, thigh pain, and radiologic analysis. Results: ≤0.01). Stable fixation was demonstrated for all implants with no change in position except for one case of Vancouver type B2 periprosthetic femur fracture. A radiolucent line (RLL) was observed in 16 hips (12.5%). Thigh pain was observed in only two hips (1.6%) at the final follow-up. There were no cases of osteolysis around the stem. The survival rate for the COREN stem was 97.7%. Conclusion: Good long-term survival with excellent clinical and radiological outcomes can be achieved using the COREN femoral stem regardless of Dorr type.

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)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.268
Teacher spread0.234 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHip & PelvisSame topicOrthopaedic implants and arthroplastyFrench-language works237,207