Iliofemoral Arthrodesis and Pseudarthrosis: A Long-Term Functional Outcome Evaluation
Bibliographic record
Abstract
Reconstruction after the resection of pelvic tumors is a major challenge. It depends on many factors such as age, activity level, type of tumor, its adjuvant treatment, and the extent of the disease. The purpose of the current study was to analyze the functional and oncologic outcomes of patients who had an iliofemoral arthrodesis after resection of a pelvic sarcoma. Between 1981 and 1999, 20 males and 12 females with a mean age of 39.9 years (range, 10-71 years) had an iliofemoral arthrodesis, either as a solid fusion or primary pseudarthrosis, at one institution. The functional outcome was evaluated using the Musculoskeletal Tumor Society and the Toronto Extremity Salvage scores. At a mean followup of 97 months (range, 14-226 months), 15 of 32 patients were alive, all without disease. The radiographic union rate was 86%. The mean overall Musculoskeletal Tumor Society and Toronto Extremity Salvage scores were 64% and 48%, respectively. Patients with a primary solid fusion did functionally better compared with patients who had pseudarthrosis (Toronto Extremity Salvage Score, 76%; Musculoskeletal Tumor Society Score, 71% versus Toronto Extremity Salvage Score, 52%; Musculoskeletal Tumor Society Score, 25%). Biomechanical analysis showed that the loss of motion in the hip is well-compensated. The authors conclude from this series that iliofemoral reconstruction after resection of a pelvic sarcoma provides acceptable and durable long-term results, not only from the oncologic, but also from the functional perspective.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".