Proximal Femoral Replacement and Allograft Prosthesis Composite in the Treatment of Periprosthetic Fractures with Significant Proximal Bone Loss
Bibliographic record
Abstract
Femoral bone loss due to periprosthetic fracture, a challenging problem in total hip arthroplasty (THA), is increasingly encountered due to a rise in the number of revision THAs performed. Allograft prosthesis composite (APC) and proximal femoral replacement (PFR) are two available options for management of patients with difficult type-B3 Vancouver periprosthetic fractures. The treatment algorithm for patients with these fractures has been extensively studied and is influenced by the age and activity level of the patient. APC is often preferred in young and active patients in an attempt to preserve bone stock while older and less active patients are considered candidates for PFR. In spite of the high rate of overall complications with these two procedures, reported survivorship is acceptable. Treating patients with these complicated fractures is fraught with complications and, even with successful treatment, the outcomes are not as promising as those associated with primary hip replacement. In this paper, we aimed to review available published reports about PFR and APC for treatment of periprosthetic fractures around THAs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".