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Record W2418699057

Does the priority scoring system for joint replacement really identify those in most need?

2005· article· en· W2418699057 on OpenAlexaboutno aff
Brendan Coleman, Stephen McChesney, Bruce Twaddle

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACJoint replacementPhysical therapyScoring systemArthroplastyJoint arthroplastyTotal joint replacementJoint (building)ArthritisFunctional impairmentOsteoarthritisSurgeryInternal medicineAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

The Priority Criteria for Major Joint Replacement Scoring System was introduced to prioritise patients on the basis of clinical and social need for surgery. The purpose of this study was to assess its correlation with the Western Ontario and McMasters Universities Arthritis Index (WOMAC) and musculoskeletal functional assessment questionnaires. Fifty patients placed on the waiting list for total joint arthroplasty were surveyed comparing the physician derived priority score and the patient-derived WOMAC and musculoskeletal functional assessment questionnaires. Results demonstrate a poor correlation between the priority scoring system and the WOMAC and musculoskeletal functional assessment. In addition, the results indicates that the priority scoring system for major joint replacement does not differentiate between severity of impairment secondary to joint disease in patients placed on the surgical waiting list for joint replacement.

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)0.003
metaresearch head score (Gemma)0.018
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 score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.274
Teacher spread0.244 · 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

Citations19
Published2005
Admission routes1
Has abstractyes

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