Fretting Wear and Corrosion-Related Risk Factors in Total Hip Replacement: A Literature Review on Implant Retrieval Studies and National Joint Replacement Registry Reports
Bibliographic record
Abstract
Fretting corrosion is a known failure mechanism of total hip replacement (THR) that can lead to revision surgery. Implant retrieval studies have thoroughly documented the occurrence of fretting corrosion in THR implants and its correlation with implant- and patient-related factors. Although implant retrieval studies benefit both clinicians and implant manufacturers, the limitations of these types of studies need to be acknowledged. For example, while some factors are routinely investigated for a possible correlation with failure due to fretting corrosion, other factors are often assumed to have no effect. To improve on these limitations, this review investigates the most significant patient- and implant-related risk factors for fretting corrosion of THR implants for both published retrieval studies and joint replacement registries. The findings and limitations are discussed critically. It is concluded that retrieval studies add significant insight into implant failure mechanisms and should be used in conjunction with joint replacement registry reports. It is suggested that the development of reliable predictive models based on implant failure risk factors and decision-making support systems could lead to enhanced implant longevity.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".