Failure Modes in Orthopedic Oncologic Reconstructive Surgery: A Review of Imaging Findings and Failure Rates
Bibliographic record
Abstract
Limb salvage surgeries utilizing endoprostheses and allografts are performed for a variety of oncologic conditions. These reconstructions can fail and require revision for many reasons, which are outlined and classified into mechanical failures (soft tissue failures, aseptic loosening, structural failure), non-mechanical failures (infection, tumor progression), and pediatric failures (physeal arrest, growth dysplasia). Distinct radiologic and clinical findings define specific failure subtypes but are sparsely illustrated in the radiology literature. Specifically, an understanding of the organizational structure of the failure modes can direct radiologists' search for post-reconstruction complications, enhance an appreciation of their prognostic significance, and facilitate research by standardizing the language and conceptual framework around outcomes. The purpose of this review is to highlight the key radiologic findings and imaging studies of each failure mode in orthopedic oncologic reconstructive surgery in the context of risk factors, failure rates, prognosis and survival statistics, and clinical decision-making regarding chemotherapy, radiation, and revision surgery.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".