AB135. 33. Role of trabecular metal augments for Paprosky type 3 defects in acetabular revision
Bibliographic record
Abstract
Background: Trabecular metal augments are one option when reconstructing bone loss during acetabular side revision surgery. Methods: We studied 38 consecutive patients with Paprosky type 3 defects that were revised using a Trabecular Metal shell and one or more augments over a 6-year period. There were 29 Paprosky type 3A defects and 9 Paprosky type 3B defects. The mean age of the patients at time of surgery was 68.2 years (range, 48–84 years). The mean length of follow-up was 36 months (range, 18–74 months). Results: The mean pre-operative SF12 improved from 27.7 before operation to 30.1 at the time of final follow-up (P=0.001). The mean Western Ontario and McMaster Universities Arthritis Index (WOMAC) score improved from 53 pre-operatively to a mean of 78.8 at final follow-up (P<0.0001). There was evidence of radiographic loosening in seven of the cup-augment constructs. One patient developed a deep infection requiring re-revision. Two patients required revision for aseptic loosening. Conclusions: The use of Trabecular Metal augments in complex acetabular reconstruction is associated with good outcome in the short to medium term.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".