[Effectiveness of acetabular revision using a metal reconstruction cage].
Bibliographic record
Abstract
Objective: To explore the clinical outcomes of acetabular revision using a metal reconstruction cage. Methods: Between October 2006 and October 2013, 16 patients (16 hips) underwent acetabular revision with a metal reconstruction cage. There were 4 males and 12 females, with the mean age of 62.7 years (range, 49-78 years). The time from total hip arthroplasty to revision was 3-15 years (mean, 8.2 years). The causes for revision were aseptic acetabular loosening in 15 cases, and femoral periprosthetic fracture (Vancouver type B3) in 1 case. According to the American Academy of Orthopaedic Surgeons (AAOS) classification, there were 12 cases of type III and 4 cases of type IV; according to the Paprosky classification, there were 12 cases of type IIIA and 4 cases of type IIIB. Harris score was used for hip function evaluation, and visual analogue scale (VAS) for pain in the thigh. X-ray films were taken for imaging evaluation. Results: =0.00). X-ray film results showed bony fusion at the osteotomy sites at 4 to 12 months after operation. No continuous radiolucent line, prosthetic dislocation, or osteolysis was found, and bony ingrowth was observed in all patients. No patient received re-revision due to prosthetic loosening. Conclusion: The metal reconstruction cage for acetabular revision can achieve good effectiveness for patients with serious bone defect.
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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 | 0.002 |
| 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 | 0.001 |
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".