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Record W2115095217 · doi:10.12927/hcpol.2006.18121

Obesity and Joint Replacement Surgery in Canada: Findings from the Canadian Joint Replacement Registry (CJRR)

2006· article· en· W2115095217 on OpenAlexaffvenueabout
Nicole A. de Guia, Naisu Zhu, Margaret Keresteci, Juqing Shi

Bibliographic record

VenueHealthcare policy · 2006
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsCanadian Institute for Health Information
Fundersnot available
KeywordsOsteoarthritisJoint replacementMedicineObesityOverweightKnee replacementArthroplastyHip replacementPhysical therapyTotal joint replacementObesity SurgeryKnee JointRisk factorJoint arthroplastySurgeryWeight lossInternal medicineAlternative medicineGastric bypassPathology

Abstract

fetched live from OpenAlex

Obesity has been strongly implicated as a risk factor for knee osteoarthritis and, in some studies, for osteoarthritis of the hip. Osteoarthritis is the most commonly reported diagnosis for joint replacement patients. In this study, we conducted analyses based on data from the Canadian Joint Replacement Registry (CJRR) to estimate the relationships between overweight and obesity and rates of joint replacement surgery in Canada. Obese persons were over three times as likely and overweight persons were one and a half times more likely to undergo joint replacement surgery, compared to those in the acceptable weight category in 2003-04. This study provides evidence of a clinically relevant association between obesity and joint replacement surgery.

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)0.006
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 score0.016
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.008
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.262
Teacher spread0.232 · 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

Citations34
Published2006
Admission routes3
Has abstractyes

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