Survival, Tumor Recurrence, and Function Following Shoulder Girdle Limb Salvage at 24 to 35 Years of Follow-up
Bibliographic record
Abstract
Limb salvage is the treatment of choice for malignant shoulder girdle tumors; however, there is a paucity of data examining the long-term outcome. The authors have previously reported on a cohort of patients at short- and mid-term follow-up. The purpose of this study was to report the long-term outcome of shoulder reconstruction in terms of oncological and functional outcome. The authors reviewed 53 patients who underwent a limb salvage procedure for treatment of a tumor of the shoulder girdle. At a mean of 28 years following the resection, 76% of surviving patients were contacted and administered functional outcome scores using the Musculoskeletal Tumor Society (MSTS) and Toronto Extremity Salvage (TESS). The 20-year survival and recurrence-free survival were 79% and 80%, respectively. Likewise, the 20-year revision survival was 75%, with a limb salvage rate of 94%. At last follow-up, the mean MSTS rating and TESS score were 75% and 85%, respectively, with 9 patients having improvement in their MSTS rating from the previous findings. Limb salvage following resection of shoulder girdle tumor resulted in acceptable means of oncological outcome and function. Some patients continued to experience improvements in functional outcome even at late (>20 years) follow-up. [Orthopedics. 2019; 42(6):e514-e520.].
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".