Large head ceramic-on-ceramic bearing in primary total hip arthroplasty: average 3-year follow-up of a multicentre study
Bibliographic record
Abstract
BACKGROUND: Surgeons are increasingly using larger femoral head sizes in total hip arthroplasty (THA) to improve stability and reduce the rate of dislocation, 1 of the leading causes of revision surgery. Large ceramic head sizes up to 48 mm can now be used with monoblock acetabular components. National registries have shown promising results at short-term with large diameter ceramic-on-ceramic THA, with very low revision rates.This study reports on the average 3-year follow up of a press-fit monoblock large diameter acetabular shell with a pre-assembled ceramic liner, with emphasis on the radiographic outcome, complications related to the implantation of the cup, and the patient's clinical outcome. METHODS: 170 hips in 169 patients were reviewed at an average 38 ± 5.8 months following surgery. RESULTS: The radiographic review revealed no acetabular cup loosening, no osteolysis and no cup migration. 1 acetabular cup was revised for malposition. The patient clinical outcome and the satisfaction rate were excellent. At 3 years, 7.1% of patients complained of groin pain and 3.5% spontaneously reported hip joint generated noise. 1 patient sustained a non-recurrent traumatic hip dislocation 2 years post surgery. CONCLUSIONS: New technology should be introduced cautiously on the market. This is especially true for the large diameter ceramic monoblock acetabular component used in this study since it involves a new acetabular component design. At short term, we have not identified new modes of failure with this implant. Longer follow-up is still needed to assess the safety of large ceramic bearing in THA.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".