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Record W2120855889 · doi:10.1302/0301-620x.95b2.28383

Using the patient’s perspective to develop function short forms specific to total hip and knee replacement based on WOMAC function items

2013· article· en· W2120855889 on OpenAlexaboutno aff
Thoralf R. Liebs, Wolfgang Herzberg, J. Gluth, W. Rüther, J Haasters, Martin Russlies, J. Hassenpflug

Bibliographic record

VenueThe Bone & Joint Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACPerspective (graphical)Function (biology)Total hip replacementPhysical therapyMedicinePhysical medicine and rehabilitationPsychologyComputer scienceOsteoarthritisArtificial intelligenceSurgeryAlternative medicine

Abstract

fetched live from OpenAlex

Although the Western Ontario and McMaster Universities (WOMAC) osteoarthritis index was originally developed for the assessment of non-operative treatment, it is commonly used to evaluate patients undergoing either total hip (THR) or total knee replacement (TKR). We assessed the importance of the 17 WOMAC function items from the perspective of 1198 patients who underwent either THR (n = 704) or TKR (n = 494) in order to develop joint-specific short forms. After these patients were administered the WOMAC pre-operatively and at three, six, 12 and 24 months' follow-up, they were asked to nominate an item of the function scale that was most important to them. The items chosen were significantly different between patients undergoing THR and those undergoing TKR (p < 0.001), and there was a shift in the priorities after surgery in both groups. Setting a threshold for prioritised items of ≥ 5% across all follow-up, eight items were selected for THR and seven for TKR, of which six items were common to both. The items comprising specific WOMAC-THR and TKR function short forms were found to be equally responsive compared with the original WOMAC function form.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.260
Teacher spread0.226 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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