Outcomes After Abductor Reattachment to Proximal Femur Endoprosthesis After Tumor Resection
Bibliographic record
Abstract
INTRODUCTION: Resection of the proximal femur raises several challenges including restoration of the abductor mechanism. Few evaluated the outcomes of different techniques of abductor fixation to the proximal femur endoprosthesis. METHODS: A retrospective review of patients who underwent proximal femoral arthroplasty with a minimum follow-up of 12 months was conducted. Patients were divided into two groups: (1) those with preserved greater trochanter (GT) reattached to the implant and (2) those with direct abductor muscle reattachment. Both groups were compared for surgical and functional outcomes. Group 1 patients were subdivided into those who received GT reinsertion using grip and cables and those reattached using sutures. RESULTS: Fifty-three patients were included with a mean follow-up of 49 months. There were 22 patients with reinserted GT and 31 patients with soft-tissue repair. The endoprosthesis revision rate was comparable between groups (P = 0.27); however, the incidence of dislocations was higher in group 2 (0/22 versus 6/31; P = 0.035). Trendelenburg gait (77% versus 74%), use of walking aids (68% versus 81%), and abductor muscle strength were comparable between both groups (P > 0.05). In group 1, 15 patients had GT reinsertion with grip and cables. Of those, five patients (33%) had cable rupture within 13 months of follow-up. GT displacement reached 12 mm at 12 months of follow-up in patients with grip and cables compared with 26 mm in patients with GT suture reinsertion (P < 0.05). DISCUSSION: Although GT preservation did not improve functional outcomes, it was associated with a lower dislocation rate despite frequent cable failure. Less displacement was observed when GT reattachment used grip and cables.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".