Metal-on-metal hip resurfacing compared with 28-mm diameter metal-on-metal total hip replacement
Bibliographic record
Abstract
A total of 219 hips in 192 patients aged between 18 and 65 years were randomised to 28-mm metal-on-metal uncemented total hip replacements (THRs, 107 hips) or hybrid hip resurfacing (HR, 112 hips). At a mean follow-up of eight years (6.6 to 9.3) there was no significant difference between the THR and HR groups regarding rate of revision (4.0% (4 of 99) vs 5.8% (6 of 104), p = 0.569) or re-operation rates without revision (5.1% (5 of 99) vs 2.9% (3 of 104), p = 0.428). In the THR group one recurrent dislocation, two late deep infections and one peri-prosthetic fracture required revision, whereas in the HR group five patients underwent revision for femoral head loosening and one for adverse reaction to metal debris. The mean University of California, Los Angeles activity scores were significantly higher in HR (7.5 (sd 1.7) vs 6.9 (sd 1.7), p = 0.035), but similar mean Western Ontario and McMaster Universities Osteoarthritis Index scores were obtained (5.8 (sd 9.5) in HR vs 5.1 (sd 8.9) in THR, p = 0.615) at the last follow-up. Osteolysis was found in 30 of 81 THR patients (37.4%), mostly in the proximal femur, compared with two of 83 HR patients (2.4%) (p < 0.001). At five years the mean metal ion levels were < 2.5 μg/l for cobalt and chromium in both groups; only titanium was significantly higher in the HR group (p = 0.001). Although revision rates and functional scores were similar in both groups at mid-term, long-term survival analysis is necessary to determine whether one procedure is more advantageous than the other.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".