Comparison of two methods of reconstruction for primary malignant tumors at the knee: A sequential cohort study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The purpose of this study was to compare the complications and functional outcome associated with the use of an irradiated allograft-implant composite or a bone-ingrowth modular tumor prosthesis for replacement of the knee joint after resection of a bone sarcoma from the distal femur or proximal tibia. METHODS: Eleven patients initially received an allograft reconstruction, followed by 64 treated with a tumor prosthesis. The primary analysis concerned reconstructive failure, defined by the requirement for removal of the original construct. Functional outcome was assessed by using the 1987 Musculoskeletal Tumor Society rating system. RESULTS: Reconstructive failure occurred in 6 of 11 (55%) allograft constructs compared with 10 of 64 (16%) tumor prostheses (P = 0.009). Failures were due to infection (2 of 11 allografts versus 4 of 64 prostheses; P = 0.2) or mechanical complications (4 of 11 allograft fractures versus 5 of 64 broken prosthetic stems and 1 aseptically loose prosthesis; P = 0.03). The limb salvage rate was 95% (61 of 64) for patients with a tumor prosthesis compared with 64% (7 of 11) for those with an allograft (P = 0.007). Patients with a tumor prosthesis had a better functional outcome with a mean score of 75% compared with 57% for those with an allograft reconstruction (P = 0.006). CONCLUSIONS: This comparative study suggests that limb salvage surgery at the knee has a better and more predictable outcome with a tumor prosthesis than with an allograft-implant reconstruction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 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".