72 – A SURVEY ON THE INCIDENCE OF PSEUDOTUMOURS WITH MOM HIP RESURFACINGS IN CANADIAN ACADEMIC CENTRES
Bibliographic record
Abstract
Purpose: Recently, there has been concern raised on the occurrence of pseudotumors after metal on metal hip resurfacing. A pseudotumor is defined as a local soft tissue mass associated with localized bony and/or tissue (muscle) destruction. The primary purpose of this study is to determine the incidence of this complication in several high volume Canadian academic centres. Method: Nine of the 11 Canadian academic centres who perform metal on metal hip resurfacings were surveyed. The number of metal on metal hip resurfacing arthroplasties performed at each centre was first determined, as were the number of those who have presented with a pseudotumour, and subsequently gone on to revision surgery. The basic demographics of the group were recorded, as were the radiographic and implant design variables for those cases presenting with a pseudotumour. Results: A sample of 3,400 hip resurfacing arthroplasties performed between 2002 and December 2008 were surveyed. Demographics were tabulated for a sub-sample of these patients. 76% were male, the mean length of follow-up was 3.02 years, mean BMI was 28.65, and mean age was 52.10 years. Three of 3,400 cases presented with a pseudotumour, an incidence of .09%. Conclusion: Although pseudotumors remain a concern after metal on metal hip resurfacing, the incidence at short to mid term follow-up is very low in this multi-centre academic survey. This information is significantly lower than what other groups have recently reported. Continued close monitoring is required in order to determine what clinical factors are at play.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".