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Record W2172559991 · doi:10.3138/ptc.2014-59

Characteristics of People with Hip or Knee Osteoarthritis Deemed Not Yet Ready for Total Joint Arthroplasty at Triage

2015· article· en· W2172559991 on OpenAlexaffvenue
Norma J. MacIntyre, Jenna A. Johnson, Nicole MacDonald, Lauren Pontarini, Kaitlyn Ross, Gorana Zubic, Sampa Samanta Majumdar

Bibliographic record

VenuePhysiotherapy Canada · 2015
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsHamilton Regional Laboratory Medicine ProgramMcMaster University
Fundersnot available
KeywordsTriageMedicineOsteoarthritisLogistic regressionPhysical therapyPsychological interventionOdds ratioArthroplastySurgeryEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To identify the characteristics of people with hip or knee osteoarthritis (OA) attending a regional triage centre for an initial consult who are deemed not yet ready for total joint arthroplasty (TJA). METHODS: Initial consultation notes (n=482) were reviewed retrospectively. Predictive variables were derived from the literature a priori, and 14 of these variables were suitable for inclusion in stepwise multiple logistic regression analyses. RESULTS: Of the 222 eligible people, 131 (59%) were deemed not yet ready for TJA. Five variables entered into the model ([Formula: see text]=133.19, p<0.001) for an overall success rate of 81.1%. Those deemed not yet ready for TJA were more likely to have knee OA (vs. hip OA; odds ratio [OR]=0.352, p=0.018), to have less severe OA (OR=0.246 for each category increase in severity, p<0.001), to use no gait aid (vs. cane; OR=0.390, p=0.033), and to have a higher Lower Extremity Functional Scale score (OR=1.050 for each 1-point increase, p=0.003) and better joint status as measured by the Knee Society Scale or Hip Harris Scale (OR=3.946 for each category increase, p=0.007). CONCLUSION: Considering these characteristics will help clinicians to identify individuals likely to require interventions other than TJA.

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)0.000
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 score0.458
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.265
Teacher spread0.239 · 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

Citations6
Published2015
Admission routes2
Has abstractyes

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