Long-Term Follow-Up in Tumoral Arthroplasty
Bibliographic record
Abstract
Abstract Introduction. Efficient management of a segmental resection or major osteolysis in the distal femur secondary to a tumor formation remains a controversial problem. Available options include the use of a modular or customized megaprosthetic implant. Modularity allows versatility for reconstruction and avoids the delay required to make a customized implant. Hypothesis and type of study. Performing a clinical and radiological retrospective study that aims to evaluate long-term efficiency in the use of megaprostheses in segmental distal femur resections. Elaboration of patient selection criteria for modular prosthesis. Materials and methods. We followed retrospectively 33 patients for 5 years from the time of the first surgery. We evaluated the implant stability, the late complications rate, and the long-term functional recovery of patients with distal femoral tumors who underwent segmental resections and subsequently reconstructive arthroplasty. Results. Thirty of the 33 patients maintained a mobile knee joint. An intermediate staging was performed at 30 months, which determined tumor recurrence in 2 patients, aseptic degradation of the components in 3 of them, and septic degradation in two of the evaluated cases. Because a tumoral recurrence occurred on the 45 th month, the need for amputation of the prosthetic limb was imposed. The degradation of the polyethylene component (in 5 cases) was observed in the 5-year assessment. The functional results were excellent with the Musculoskeletal Tumor Society Score of 88% and a Toronto Extremity Severity Scale Score of 94%. Conclusions. Patients with distal femoral bone tumors undergoing modular reconstruction prosthetic arthroplasty have excellent functional results with retaining the affected limb and knee mobility. There was a close correlation between correctly applying the selection criteria for patients undergoing prosthesis intervention and functional recovery results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".