OUTCOMES FOLLOWING REVISION OF LARGE DIAMETER METAL-ON-METAL TOTAL HIP REPLACEMENTS FOR ADVERSE LOCAL TISSUE REACTION
Bibliographic record
Abstract
High failure rates have been associated with large diameter metal-on-metal total hip replacements (MoM THR). However there is limited literature describing the outcomes following the revision of MoM THR for adverse local tissue reaction (ALTR). A total of 98 large diameter MoM THRs underwent revision for ALTR at our institution. The data was obtained from the clinical records and included the demographics, intra-operative findings of ALTR and post-operative complications. Any subsequent procedures and re-revision for any reason was analysed in detail. The clinical outcome was measured using functional outcome scores using the Oxford hip score (OHS), Western Ontario and McMaster Universities osteo-arthritis index (WOMAC) score and Short Form (SF12). The mean age of the patients at the time of revision was 58.2 yrs. At a mean follow-up of 3.9 years (1.0 to 8.6) from revision for ALTR, there were 15 hips (15.3 %) with post-operative complications and 8 hips (8 %) requiring re-revision. The Kaplan–Meier five-year survival rate for ALTR revision was 91 % (95% confidence interval 78.9 to 98.0). There were no statistically significant predictors of re-revision. The rate of postoperative dislocation following revision was 9.2% (9 hips). The post-operative functional outcome depends on the intra-operative findings of tissue destruction secondary to ALTR. The short term results following revision of large diameter MoM THR for ALTR are comparable with other reports in the literature. The use of constrained liners reduces the incidence of post-operative dislocation. There is an increased risk of postoperative instability following revision THR for ALTR. Early identification and intervention seems to be the logical approach in the management of patients with ALTR.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".