CORR Insights®: Metal-on-conventional Total Hip Arthroplasty Bearing Surfaces Have a Higher Risk of Revision Than Metal-on-highly Crosslinked Polyethylene: Results From a US Registry
Bibliographic record
Abstract
Where Are We Now? Highly crosslinked polyethylene (XLPE) has essentially supplanted conventional polyethylene for use in total hip arthroplasty (THA) during the past decade. There now exists good evidence to demonstrate a clear reduction in femoral head penetration (and presumably polyethylene wear) and periprosthetic osteolysis associated with the use XLPE compared to conventional polyethylene in THA [2, 3]. While the annual reports of Australian Orthopaedic Association National Joint Replacement Registry continue to show the clinical benefits of XLPE (demonstrating a reduction in revision rates) [1], other investigators have not demonstrated a clear reduction in revision rates with the use of XLPE at mid-term followup [4]. The current study by Paxton and colleagues attempts to demonstrate the clinical benefits resulting from the use of XLPE compared to conventional polyethylene through the analysis of a large US-based patient database. Their findings demonstrate that, for two specific implant designs, the revision rate was significantly decreased for XLPE compared to the use of conventional polyethylene. Therefore, this work essentially confirms the experience reported by the Australian Orthopaedic Association National Joint Replacement Registry during the past decade. While important work, this study is limited by the observational nature of the study, inherent to all registry or database analysis, and only provides information about two specific hip designs (both of which having been replaced by more recent designs by their respective manufacturers). Furthermore, analysis of this type does not provide any radiological, functional or patient-derived outcomes comparing the two polyethylene materials. Where Do We Need To Go? Clearly, longer-term followup is required to confirm the benefits of XLPE. Additionally, what is lacking through the examination of large database and joint registry data is the ability to determine the potential effect of many specific variables to the performance of XLPE. These variables include: Surgical approach, surgeon experience, implant design, the specific properties of the XLPE, femoral head size, as well as patient factors including gender, race, and activity level. How Do We Get There? In order to seek the answers that we require, specifically, to show the clear long-term clinical benefits associated with the use of XLPE, there needs to be ongoing surveillance and reporting of long-term results from existing databases as well as the creation of national and/or large population-based registries, particularly from North America. Where it exists, the inclusion of validated patient outcome scores and/or functional scores, in addition to survivorship data (revision rates) should be reported. Additionally, researchers must continue to report on previously initiated randomized controlled trials comparing XLPE to conventional polyethylene in order to demonstrate the long-term benefits and ensure there are no long-term unexpected deleterious results associated with XLPE. The creation of new randomized controlled trials to compare XLPE with conventional polyethylene is arguably unethical at this point in time with the already-strong evidence to support the ongoing use of XLPE for THA. Long-term followup is required through ongoing surveillance (at 15 years to 20 years and beyond) with the addition of cross-sectional imaging (CT scan) to quantify periarticular osteolysis, which is perceived as an important precursor to implant failure.
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 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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.005 | 0.002 |
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".