Whole Span Plating Prevents Subsequent Ipsilateral Femoral Fractures After Peri-Implant Fixation: A Preliminary Report
Bibliographic record
Abstract
Background: Peri-implant femoral fractures are increasingly prevalent among the elderly, often leading to re-fractures due to osteoporosis and implant stress. Whole span plating (WSP) has been proposed as a surgical approach to mitigate this risk. Methods: A retrospective study was conducted on 10 patients (mean age: 79.5 years) who underwent WSP for peri-implant femoral fractures between April 2020 and March 2023. Fractures were classified using the Vancouver, NPPIF, and Lewis and Rorabeck systems. Surgical indication required meeting at least two of the following criteria: age ≥ 70 years, history of fragility fracture(s), high fall risk, severe osteoporosis, extensive fracture pattern, or no implant loosening. Results: No re-fractures were observed during a mean follow-up period of 14.5 months. Although 90% of patients required red blood cell transfusions (mean volume: 3.8 units), early weight-bearing was achieved in most cases. Four patients had received osteoporosis treatment, highlighting the need for integrated bone health management. Conclusions: WSP appears to be a feasible and safe surgical option for high-risk patients with peri-implant femoral fractures, potentially reducing the incidence of subsequent fractures. Further studies with larger cohorts and longer follow-up are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".