Functional Outcomes and Complications After Oncologic Reconstruction of the Proximal Humerus
Bibliographic record
Abstract
BACKGROUND: No consensus exists on the best method of articular reconstruction in patients who require proximal humerus resection for the management of primary bone sarcomas, soft-tissue sarcomas extending into the bone, benign and locally aggressive primary bone tumors, and metastatic disease. METHODS: We identified patients from two institutions who underwent wide resection of the proximal humerus along with oncologic reconstruction using osteoarticular allografts (OAs), endoprostheses, or allograft-prosthesis composites. We prospectively collected functional outcomes and retrospectively assessed complications and implant survival. RESULTS: A total of 150 patients were included in this study. The average Disabilities of the Arm, Shoulder and Hand questionnaire score was 26 for 25 patients, of which we gathered their functional data, with no differences in physical function among the three constructional methods according to the Disabilities of the Arm, Shoulder and Hand questionnaire, upper extremity Toronto Extremity Salvage Score, upper extremity Musculoskeletal Tumor Society, and Patient-Reported Outcomes Measurement Information System scores. Overall, the survival rate of the prosthesis was >50%. A trend was noted for a higher risk of failure in the OA group secondary to the allograft fracture. DISCUSSION: All three articular oncologic shoulder reconstructions were comparable in terms of function. This large series confirms a higher fracture rate in OAs, which explains the observed higher revision rate and apparent lower survival rate in this subgroup.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".