The push-through total femoral prosthesis offers a functional alternative to total femoral replacement: a case series
Bibliographic record
Abstract
PURPOSE: Oncologic resections or complications of segmental femoral prostheses can result in severe bone loss of the femur for which a total femoral prosthesis (TFP) is required. This study assesses whether the loss of stability and function caused by the loss of muscle attachments can be improved by using a push-through total femoral endoprosthesis (PTTF), because it saves parts of the femur and its muscle attachments. METHODS: In this retrospective case series, ten patients aged 25-77 (mean 54) who received a PTTF between 2005 and 2014 were included for baseline, complications and survival analysis with a mean follow-up of 5.3 (1.1-9.6) years. Functional outcome was assessed in six patients using the Musculoskeletal Tumor Society (MSTS) score, WHO performance scale, Toronto Extremity Salvage Score (TESS), SF36, EQ-5D, NRS pain score, fatigue score and satisfaction score. RESULTS: The mean MSTS score was 64% (23-93%). Five patients had a WHO performance scale of 1, one patient of 3. Mean TESS was 69% (13-90%). SF36 was most notably limited by physical functioning (mean 48), vitality (68) and general health (67). NRS score was 1.9, 1.8 and 8.3 for pain, fatigue and satisfaction, respectively. There were four failures: two infections (one resulting in amputation and one in a minor revision) and two mechanical failures (which required one revision to a TFP and one minor revision). Patient survival was 100%, limb survival 90%, and prosthesis survival 80%. CONCLUSION: The push-through total femoral endoprosthesis allows preservation of muscle attachments and offers a good alternative to total femoral prostheses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".