Distal femur fractures in the elderly population treated with fibular allograft and lateral plating only: the surgical technique
Bibliographic record
Abstract
Distal femoral fractures are increasingly observed in the elderly population, often presenting with osteoporotic bone characteristics. Surgical fixation remains the gold standard, with lateral locking plates being the most commonly used method. To prevent hardware failure and varus collapse in osteoporotic bone, various surgical techniques and augmentation strategies have been proposed. We describe a surgical technique for managing osteoporotic, comminuted distal femur fractures using a fibular strut allograft in combination with a lateral-only locking plate, along with outcomes in patients treated with this approach. When an intra-articular component was present, it was addressed first. Through the zone of comminution and a cortical window created in the lateral condyle, a fibular strut allograft was inserted into the femoral canal extending into the epiphysis. Once satisfactory alignment and reduction were confirmed radiographically, a lateral locking plate was applied, bridging any existing proximal implants. Proximal screws were inserted percutaneously, while multiple screws were directed through the fibular graft for enhanced stability. The combination of a fibular strut allograft with a lateral locking plate offers a reliable option for treating comminuted distal femur fractures with osteoporotic features, minimizing displacement and reducing the risk of implant failure without necessitating additional medial support or secondary implants.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".