Clinical Outcome After Replacement of Distal Femur/Proximal Tibia in a Heterogeneous Patient Cohort: Function Following Tumour, Trauma, and Loosening
Bibliographic record
Abstract
BACKGROUND: Distal femur and proximal tibia replacements as limb-salvage procedures with good outcome parameters for patients with tumours have been broadly described. However, the overall midterm outcome in a mixed, heterogeneous patient collective is still unclear. PATIENTS AND METHODS: We retrospectively analysed 59 consecutive patients (33 for primary and 26 for revision surgery) between 1998 and 2017. Indication for implantation was tumour (n=16), periprosthetic fracture (n=14), traumatic fracture (n=14), infection (n=10), aseptic loosening (n=3), and pathological fracture (n=2). The mean follow-up duration was 3 years. Clinical functions were evaluated by Toronto Extremity Salvage Score and Knee Society Score. Knee extension and flexion force were measured. RESULTS: The overall survival rate of arthroplasties was 59% (n=35). Major complications were observed in 36 (61%) patients. During the follow-up period, 14 (24%) patients died. We recorded periprosthetic joint infection in 21 (36%) patients, recurrence of tumour in two (3%), and aseptic implant failure in three (5%). The mean Toronto Extremity Salvage Score was 66±33, and the mean Knee Society Score was 49±30. The mean extension force on the operated side was significantly reduced at 60° and 180° compared to the healthy side (p=0.0151 and p=0.0411, respectively). CONCLUSION: Distal femur and proximal tibia replacements showed limited clinical function in a heterogeneous patient collective. Indication for implantation should be considered carefully.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".