Hip Resurfacing Compared with 28-mm Metal-on-Metal Total Hip Replacement
Bibliographic record
Abstract
BACKGROUND: Bone stock conservation, hip anatomy preservation, and greater stability are among the promoted advantages of hip resurfacing (HR). However, the disappointing failure of some implants nearly led to its abandonment. The aim of this study was to compare clinical scores and revision and complication rates after HR with those after total hip arthroplasty (THA). METHODS: Two hundred and three hips were randomized to 28-mm metal-on-metal (MoM) THA (99 hips) or to HR (104 hips). Main outcome measures compared between groups were the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, the revision rate, and the complication rates. The radiographic findings were also assessed. RESULTS: After a mean follow-up of 15 years (range, 14 to 16 years), 9 (4.4%) of the 203 patients were lost to follow-up and 15 (7.4%) had died. The Kaplan-Meier survivorship, with revision for any reason as the end point, was 89.2% (95% confidence interval [CI], 82.3% to 96.1%) for HR and 94.2% (95% CI, 89.3% to 99.1%) for THA (p = 0.292). The reasons for revision included infection (3 patients), recurrent dislocation (1 patient), and adverse reaction to metal debris (ARMD) (1 patient) in the THA group and ARMD (2 patients) and femoral head loosening (7 patients) in the HR group. With aseptic revision as the end point, the Kaplan-Meier survivorship was significantly higher in the THA group (97.4% versus 89.2%; p = 0.033). No dislocation occurred in the HR group compared with 4 in the THA group (p = 0.058). Both groups achieved a similar mean WOMAC score (10.7 in the HR group and 8.8 in the THA group; p = 0.749), Forgotten Joint Score (87.1 and 85.3, respectively; p = 0.410), University of California Los Angeles (UCLA) activity score (6.3 and 6.4, respectively; p = 0.189), and overall joint perception (p = 0.251). CONCLUSIONS: The specific HR and MoM 28-mm THA implants used in this study showed good long-term survival and function. The overall rates of complications and revisions were similar in both groups but were of different types. As it provides better femoral bone preservation and biomechanical reconstruction, HR may continue to have a role in selected patients when performed by experienced surgeons and using validated implants. LEVEL OF EVIDENCE: Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.004 |
| 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 | 0.001 |
| 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".