Timing of total joint replacement affects clinical outcomes among patients with osteoarthritis of the hip or knee
Bibliographic record
Abstract
OBJECTIVE: To determine the predictors of outcome in patients with osteoarthritis 2 years after receiving total hip or knee replacement. METHODS: A prospective cohort study of 222 osteoarthritis patients undergoing total hip or knee replacement in Boston and Montreal was done. Their postoperative outcomes at 6 months were previously reported. This followup reports on the outcomes after 2 years among the 165 patients (74%) who remained. The subjects were divided into 2 groups according to the median value of their preoperative Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function score. The Short Form 36-item physical function subscale and the WOMAC pain and function subscale scores were collected at baseline and at 3, 6, and 24 months postoperatively. Clinical outcomes were analyzed at 2 years, using descriptive and multiple regression analyses. RESULTS: Improvements in pain and function at 2 years were similar to those observed at 6 months. Those subjects with the worst function and pain at the time of surgery (baseline) had comparatively worse function 2 years after surgery. CONCLUSION: In this comparison, the poor outcomes observed at 6 months following total joint replacement in patients with worse baseline functional status persisted after 2 years. Although there are no validated indications for when a patient should optimally have total joint replacement, these data suggest that timing of surgery may be more important than previously realized and, specifically, that performing surgery earlier in the course of functional decline may be associated with better outcome.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".