Sandwiched Strut Allografts with Stem Retention to Treat Fragile Periprosthetic Femoral Fractures: A Case Report
Bibliographic record
Abstract
Managing periprosthetic femoral fractures is challenging, particularly in osteoporotic patients with fragile bones. Revision with a long stem is commonly considered but may fail to provide adequate fixation and stability in fragile bones. A novel approach using sandwiched strut allografts and controlled bone crushing with robust cable fixation can offer mechanical support and provide secondary stability to the loosened femoral stem and can be considered a treatment option for low-demand patients. A 73-year-old female with 23 years of hemodialysis experienced pain and instability in her right thigh following a slip. She had extremely low bone mineral density, and radiographs revealed a periprosthetic femoral fracture with a loosened femoral prosthesis, classified as Vancouver type B3. The patient underwent surgical fixation using a long anatomical plate augmented with dual strut allografts sandwiched anterior and posterior femur. Robust cable fixation was performed to partially crush the native cortical bone against the stem to enhance stability. Postoperative imaging at 18 months confirmed successful bone union and implant stability, and the patient regained preoperative functional capacity without pain. This case demonstrates that partially crushing native bone with dual strut allografts may provide stability to the loosened femoral stem and can be an effective alternative to long-stem revision surgery for patients with highly fragile bones. This approach may provide immediate mechanical stability and can be a potential treatment option for managing fragile periprosthetic femoral fractures.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".