What advantage is there to be gained using large modular metal-on-metal bearings in routine primary hip replacement?
Bibliographic record
Abstract
The aim of this study was to investigate the possible benefit of large-head metal-on-metal bearing on a stem for primary hip replacement compared with a 28 mm diameter conventional metal-on-polyethylene bearing in a prospective randomised controlled trial. We investigated cemented stem behaviour between these two different bearings using Einzel-Bild-Röntgen-Analyse, clinical and patient reported measures (Harris hip score, Western Ontario and McMaster Universities osteoarthritis index, Short Form-36 and satisfaction) and whole blood metal ion levels at two years. A power study indicated that 50 hips were needed in each group to detect subsidence of > 5 mm at two years with a p-value of < 0.05. Significant improvement (p < 0.001) was found in the mean clinical and patient reported outcomes at two years for both groups. Comparison of outcomes between the groups at two years showed no statistically significant difference for mean stem migration, clinical and patient reported outcomes; except overall patient satisfaction which was higher for metal-on-metal group (p = 0.05). Metal ion levels were raised above the Medicines and Healthcare products Regulatory Agency advised safety level (7 µg per litre) in 20% of the metal-on-metal group and in one patient in metal-on-polyethylene group (who had a metal-on-metal implant on the contralateral side). Two patients in the metal-on-metal group were revised, one for pseudotumour and one for peri-prosthetic fracture. Use of large modular heads is associated with a risk of raised whole blood metal ion levels despite using a proven bearing from resurfacing. The head-neck junction or excess stem micromotion are possibly the weak links warranting further research.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".