OUTCOMES FOLLOWING A TOTAL FEMORAL PLATING TECHNIQUE FOR MANAGEMENT OF PERIPROSTHETIC FRACTURES AROUND STABLE HIP AND KNEE IMPLANTS
Bibliographic record
Abstract
Introduction Management of Vancouver type B1 and C periprosthetic fractures in elderly patients requires fixation and an aim for early mobilisation but many techniques restrict weightbearing due to re-fracture risk. We present the clinical and radiographic outcomes of our technique of total femoral plating (TFP) to allow early weightbearing whilst reducing risk of re-fracture. Methods A single-centre retrospective cohort study was performed including twenty-two patients treated with TFP for fracture around either hip or knee replacements between May 2014 and December 2017. Follow-up data was compared at 6, 12 and 24 months. Primary outcomes were functional scores (Oxford Hip or Knee score (OHS/OKS)), Quality of Life (EQ-5D) and satisfaction at final follow-up (Visual Analogue Score (VAS)). Secondary outcomes were radiographic fracture union and complications. Results Mean OHS and OKS was 50.25, EQ-5D score was >4 for all modalities, VAS was 64.4/100. Radiographs demonstrated bony union in 58% at 3 months and 76% at 6 months. We identified no case of re-fracture however non-union occurred in 4 patients. No other operative complications were identified. Conclusion These results suggest that TFP may be a safe, viable option for management of periprosthetic fractures around stable implants allowing the benefit of early weightbearing, satisfactory outcomes and low re-fracture risk.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".