Patient-reported outcome in total hip replacement
Bibliographic record
Abstract
Our aim was to define the minimum set of patient-reported outcome measures which are required to assess health status after total hip replacement (THR). In 114 patients, we compared the pre-operative characteristics and sensitivity to change of the Oxford hip score (OHS), the Western Ontario and McMaster Universities osteoarthritis index (WOMAC), the SF-36, the SF-12 (derived from the SF-36), and the Euroqol questionnaire (EQ-5D). At one year after operation, very large effect sizes were found for the disease-specific measures, the physical domains of the SF-12, SF-36 and the EQ-5Dindex (1.3 to 3.0). Patients in Charnley class A showed more change in the OHS, WOMAC pain and function, the physical domains of the SF-36 and the EQ-5Dvas (p < 0.05) compared with those in the Charnley B and C group. In this group, the effect size for the OHS more than doubled the effect sizes of WOMAC pain and physical function. We found high correlations and correlations of change between the OHS, the WOMAC, the physical domains of the SF-12 and the SF-36 and EQ-5Dindex. The SF-36 and EQ-5D scores at one year after operation approached those of the general population. Furthermore, we found a binomial distribution of the pre-operative EQ-5Dindex score and a pre-operative discrepancy and post-operative agreement between the EQ-5Dvas and EQ-5Dindex. We recommend the use of the OHS and SF-12 in the assessment of THR. The SF-36 may be used in circumstances when smaller changes in health status are investigated, for example in the follow-up of THR. The EQ-5D is useful in situations in which utility values are needed in order to calculate cost-effectiveness or quality-adjusted life years (QALYs), such as in the assessment of new techniques in THR.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".