Despite higher revision rate, MoM large-head THA offers better clinical scores than HR: 14-year results from a randomized controlled trial involving 48 patients
Bibliographic record
Abstract
BACKGROUND: The high failure rates of metal on metal (MoM) large diameter head total hip arthroplasty (LDH THA) and hip resurfacing (HR) prevented their long-term comparisons with regards to clinical outcome. Such knowledge would be important as ceramic LDH bearing is now available. With long-term follow-up, we investigated the difference in 1) patient-reported outcome measures (PROMs); 2) revision and adverse events rates, and 3) metal ion levels between MoM LDH THA and HR. METHODS: Forty-eight patients were randomized for LDH THA (24) or HR (24) with the same MoM articulation. At a mean follow-up of 14 years, we compared between groups different PROMs, the number of revisions and adverse events, whole blood Cobalt (Co) and Chromium (Cr) ion levels, and radiographic signs of implant dysfunction. RESULTS: LDH THA (all cases: revised and well-functioning) had significantly better WOMAC (94 versus 85, p = 0.04), and more frequently reported having no limitation (p = 0.04). LDH THA revision rate was 20.8% (5/24) versus 8.3% (2/24) for HR (p = 0.4). Mean Co and Cr ion levels were higher in LDH THA compared to the HR (Co: 3.8 μg/L vs 1.7 μg/L; p = 0.04 and Cr: 1.9 μg/L vs 1.4 μg/L, p = 0.1). On radiographic analyses, 2 LDH THAs showed signs of adverse reaction to metal debris, whereas 1 loose femoral HR component was documented. CONCLUSION: In the long-term, MoM LDH THA had a high trunnion related revision rate but nonetheless showed better PROMs compared to HR. Provided with a well-functioning modular junction, non-MoM LDH THA would offer an appealing option. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT04516239 ), August 18, 2020. Retrospectively registered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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) | 0.001 | 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 teacher head, 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".