A Review of Periprosthetic Femoral Fractures Associated With Total Hip Arthroplasty
Bibliographic record
Abstract
Periprosthetic fractures of the femur in association with total hip arthroplasty are increasingly common and often difficult to treat. Patients with periprosthetic fractures are typically elderly and frail and have osteoporosis. No clear consensus exists regarding the optimal management strategy because there is limited high-quality research. The Vancouver classification facilitates treatment decisions. In the presence of a stable prosthesis (type-B1 and -C fractures), most authors recommend surgical stabilization of the fracture with plates, strut grafts, or a combination thereof. In up to 20% of apparent Vancouver type-B1 fractures, the femoral stem is loose, which may explain the high failure rates associated with open reduction and internal fixation. Some authors recommend routine opening and dislocation of the hip to perform an intraoperative stem stability test to rule out a loose component. Advances in plating techniques and technology are improving the outcomes for these fractures. For fractures around a loose femoral prosthesis (types B2 and 3), revision using an extensively porous-coated uncemented long stem, with or without additional fracture fixation, appears to offer the most reliable outcome. Cement-in-cement revision using a long-stem prosthesis is feasible in elderly patients with a well-fixed cement mantle. It is essential to treat the osteoporosis to help fracture healing and to prevent further fractures. We provide an overview of the causes, classification, and management of periprosthetic femoral fractures around a total hip arthroplasty based on the current best available evidence.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".