Characteristics of People with Hip or Knee Osteoarthritis Deemed Not Yet Ready for Total Joint Arthroplasty at Triage
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".