Waiting for hip revision surgery: the impact on patient disability.
Bibliographic record
Abstract
OBJECTIVE: Increased wait times for total joint arthroplasty (TJA) are a concern nationally and provincially. Additionally, the number of patients requiring revision of their initial TJA is increasing. The purpose of this study was to evaluate the wait times and impact of waiting for revision TJA. METHODS: We followed 127 revision hip arthroplasty patients (mean age 68 y) prospectively while they waited for surgery. We collected Western Ontario and McMaster Universities Osteoarthritis Index (pain, stiffness and physical function) data at the decision for surgery and at 6-month intervals until surgery. RESULTS: The mean wait time for surgery was 123.8 days (mean wait times for individual surgeons ranged from 7 to 213 d). Of the patients, 106 waited < 6 months, 12 waited 6-12 months and 9 waited > 12 months. Wait times evaluated up to 6 months, 6-12 months or > 12 months demonstrated significant increases in pain (F = 7.12, p = 0.01), with a mean change of 2.6 points when patients waited > 6 months. Physical disability increased (F = 4.61, p = 0.01), with a mean change of 5.1 points when the wait time was 6-12 months and 8.8 points when the wait time was > 12 months. CONCLUSION: Waiting > 6 months for revision hip arthroplasty resulted in significant increases in pain and physical disability.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".