Stringent Patient Selection in Bulk Allograft Reconstructions
Bibliographic record
Abstract
We hypothesized that stringent patient selection in the use of large bulk structural allografts for limb preservation would positively affect outcomes and decrease complication rates by eliminating certain comorbid or social factors known to contribute to the most detrimental sources of allograft failure: infection, fracture, and nonunion.Our selection criteria included patients who were younger than 50 years, nonsmokers, non-obese (body mass index <40), who did not receive radiation therapy to the recipient site perioperatively, and who underwent intercalary allograft reconstruction except in the upper extremity where osteoarticular allografts were permitted. Outcomes were assessed using the Musculoskeletal Tumor Society (MSTS) and Toronto Extremity Salvage Score (TESS) scoring systems. Twenty-three patients fulfilled our cohort inclusion criteria. The overall survival rate for the 23 allografts was 91% (21/23). Average MSTS and TESS scores were 76% and 87%, respectively. Eleven of 23 patients experienced at least 1 complication requiring a second procedure. Musculoskeletal Tumor Society scores among patients experiencing no complications averaged 83% vs 71% for patients experiencing at least 1 complication. Average TESS scores were 89% and 86%, respectively.The results of our early experience indicate there is no appreciable difference in complication rates among our series of patients stringently selected for bulk allograft reconstruction compared to other previously reported studies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".