New Insights into Wear and Biological Effects of Metal-on-Metal Bearings
Bibliographic record
Abstract
Update This article was updated on May 13, 2011, because of previous editorial errors. On page 76, the affiliation that had previously read “Departments of Mechanical Engineering Surgery, and Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada” now reads “Departments of Mechanical Engineering, Surgery & Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada.” On page 79, the line that had previously read “The percentage of these needle-shaped particles was the highest with hip replacements implanted for more than twenty years38,” now reads “The percentage of these needle-shaped particles was the highest with hip replacements implanted for more than twenty years (average [and standard deviation] of 28% ± 9%)38.” On page 80, the previous incorrect version of Figure 3 has been replaced with the correct version. On page 82, the last line in reference 15, which had previously read “Paper no. 214,” now reads “Paper no. 365.” An erratum has been published: J Bone Joint Surg Am 2011;93(12):1158. Background: Despite the renewed interest in metal-on-metal implants in the past two decades, the underlying wear mechanisms and biological effects are still not fully understood. Methods: This paper first reviews the tribology of metal-on-metal bearings, bringing new insights into the interaction of wear and corrosion, and putting the characteristics and the potential origin of wear particles in perspective with the proposed wear mechanisms. It then summarizes the current knowledge on the biological effects of particles and metal ions in relation to these wear mechanisms. Results: Tribochemical reactions play an important role in the wear of metal-on-metal joints. The generated tribomaterial, which progressively forms by mechanical mixing of the uppermost nanocrystalline zone of the metal surface with proteins from the synovial fluid, governs the wear rate and influences the corrosive behavior of the bearing. Nanometer-sized wear particles may initially originate from the passivation layer covering the implant surface and then detach from this tribolayer. The inflammatory response observed surrounding metal-on-metal implants appears to be lower than that around metal-on-polyethylene implants. However, metallic byproducts, which can complex with proteins, may lead to a T lymphocyte-mediated hypersensitivity response. Conclusions: The tribolayer appears to have beneficial effects on the wear rate. Much information has been gained on wear particle characteristics, but the exact mechanisms of particle detachment remain to be further elucidated. Excessive wear along with a hypersensitivity response may be at the origin of the early adverse tissue reactions that have been recently reported in some patients with metal-on-metal implants. Clinical Relevance: Future development of new methods to improve the tribolayer retention and optimize the tribocorrosive properties of the implant may minimize the clinical impact of implant wear and immune responses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".