Predictors of quality of life outcomes after revision total hip replacement
Bibliographic record
Abstract
A prospective cohort of 222 patients who underwent revision hip replacement between April 2001 and March 2004 was evaluated to determine predictors of function, pain and activity level between one and two years post-operatively, and to define quality of life outcomes using validated patient reported outcome tools. Predictive models were developed and proportional odds regression analyses were performed to identify factors that predict quality of life outcomes at one and two years post-operatively. The dependent outcome variables were the Western Ontario and McMaster Osteoarthritis Index (WOMAC) function and pain scores, and University of California Los Angeles activity scores. The independent variables included patient demographics, operative factors, and objective quality of life parameters, including pre-operative WOMAC, and the Short Form-12 mental component score. There was a significant improvement (t-test, p < 0.001) in all patient quality of life scores. In the predictive model, factors predictive of improved function (original regression analyses, p < 0.05) included a higher pre-operative WOMAC function score (p < 0.001), age between 60 and 70 years (p < 0.037), male gender (p = 0.017), lower Charnley class (p < 0.001) and aseptic loosening being the indication for revision (p < 0.003). Using the WOMAC pain score as an outcome variable, factors predictive of improvement included the pre-operative WOMAC function score (p = 0.001), age between 60 and 70 years (p = 0.004), male gender (p = 0.005), lower Charnley class (p = 0.001) and no previous revision procedure (p = 0.023). The pre-operative WOMAC function score (p = 0.001), the indication for the operation (p = 0.007), and the operating surgeon (p = 0.008) were significant predictors of the activity assessment at follow-up. Predictors of quality of life outcomes after revision hip replacement were established. Although some patient-specific and surgery-specific variables were important, age, gender, Charnley class and pre-operative WOMAC function score had the most robust associations with 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 | 0.001 | 0.005 |
| 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 | 0.000 | 0.001 |
| 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".