FIVE-YEAR SURVIVORSHIP OF CERAMIC-ON-CERAMIC HIP RESURFACING: AN INTERNATIONAL MULTICENTRE STUDY
Bibliographic record
Abstract
Metal-on-metal (MoM) hip resurfacing (HR) has shown excellent results in male patients with adequate head size and suitable morphology. However, due to the long-term risk of adverse tissue reactions, particularly in females as well as limitations in component sizes, ceramic-on-ceramic (CoC) HRA has been introduced as an alternative. This study aims to examine overall survivorship and the effect of gender and component sizes on the five-year survivorship of the ReCerf CoC HRA. An international retrospective analysis was conducted on 604 consecutive patients (330 males, 264 females) with a mean age of 50.1 years (range 20–80 years) who underwent CoC HR from 3 September 2018 to 4 June 2024. All revisions were captured, and no patients were lost to follow-up. Kaplan-Meier analysis was used to determine the survivorship at 5 years. Cox proportional hazards model was used to analyse the influence of gender and implant size on the risk of revision. At a mean follow-up of 3.6 years (range: 2.4–5.7 years), the 5-year survivorship was 98.2% (95% CI 96.7–99.0%). The 5-year survivorship rates were 98.1% for males (95% CI 95.7–99.1%), 98.4% for females (95% CI 95.7–99.4%), 98.4% for femoral head sizes ≤ 48 mm (95% CI 95.9–99.4%), and 98% for head sizes ≥ 48 mm (95% CI 95.6–99.1%). Multivariate analysis indicated that neither sex nor smaller head sizes had a statistically significant impact on revision risk: males had an odds ratio (OR) of 1.2 (95% CI 0.21–6.9, p-value 0.84), and an increase in head diameter by 1 mm was associated with an OR of 1.0 (95% CI 0.81–1.23, p-value 0.99). CoC HRA demonstrates excellent survivorship at 5 years, irrespective of gender or implant size. This compares favourably to previously published outcomes for MoM HR, which typically report lower survivorship in female patients and smaller component sizes. Longer-term follow-up is required to confirm these outcomes.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".