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Record W2311561700 · doi:10.1302/0301-620x.93b3.25876

Does morbid obesity affect the outcome of total hip replacement?

2011· article· en· W2311561700 on OpenAlexaffabout
Richard W. McCalden, Kory D. Charron, Steven J. MacDonald, Robert B. Bourne, Douglas D.R. Naudie

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2011
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineMorbidly obeseBody mass indexObesityOsteoarthritisMorbid obesitySepsisAffect (linguistics)Survivorship curveSurgeryTotal hip replacementPhysical therapyInternal medicineWeight lossPsychology

Abstract

fetched live from OpenAlex

We evaluated the outcome of primary total hip replacement (THR) in 3290 patients with the primary diagnosis of osteoarthritis at a minimum follow-up of two years. They were stratified into categories of body mass index (BMI) based on the World Health Organisation classification of obesity. Statistical analysis was carried out to determine if there was a difference in the post-operative Western Ontario and McMaster Universities osteoarthritis index, the Harris hip score and the Short-Form-12 outcome based on the BMI. While the pre- and post-operative scores were lower for the group classified as morbidly obese, the overall change in outcome scores suggested an equal if not greater improvement compared with the non-morbidly obese patients. The overall survivorship and rate of complications were similar in the BMI groups although there was a slightly higher rate of revision for sepsis in the morbidly obese group. Morbid obesity does not affect the post-operative outcome after THR, with the possible exception of a marginally increased rate of infection. Therefore withholding surgery based on the BMI is not justified.

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)0.004
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.241
Teacher spread0.207 · 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

Citations125
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Bone and Joint Surgery - British VolumeSame topicOrthopaedic implants and arthroplastyFrench-language works237,207