Complications and Outcome of Bone Sarcoma Patients with Limb Salvage using Liquid Nitrogen-treated Bone for Reconstruction.
Bibliographic record
Abstract
Introduction: The recommended treatment method for bone sarcoma is wide local excision and reconstruction to preserve limb function. Established methods of reconstruction are mega prosthesis or biological reconstruction. This study aimed to determine the complications and functional outcomes associated with limb salvage surgery using liquid nitrogen-treated bone. Materials and Methods: We retrospectively observed the short-term outcome of limb salvage surgeries where liquid nitrogen bone was used for reconstruction. A total of 15 patients underwent reconstruction with liquid nitrogen auto graft from January 2018 to December 2020. We used the free freezing method of liquid nitrogen treatment after wide local excision of sarcoma. We observed short-term outcomes after liquid nitrogen-treated bone reconstruction in limb salvage surgery. Survival of the auto grafts was recorded using the Kaplan-Meier method with a 95% confidence interval. Results: The mean follow-up was 19.83 ± 4.5 months. The mean musculoskeletal tumor society score was 62.4 ± 7.9%, while the average Toronto extremity score was 59.6 ± 5.7%. Three patients died during the study duration due to visceral metastasis. Skin necrosis and wound breakdown were major complications in 9 (60%) patients. Deep infection was observed in 4 (26.7%). Similarly, 4 (26.7%) patients had non-union at either the proximal or distal osteotomy site, while the average time of bone union in the rest of the patients was 6.3 ± 1.7 months. A total of 6 (40%) patients underwent reoperation after liquid nitrogen treatment, either due to infection or non-union at the osteotomy site. Recurrence was observed in 3 (20%) of patients. Conclusion: We observed a high complication rate with liquid nitrogen-treated autograft reconstruction. Vascularized fibula with liquid nitrogen-treated autograft or endoprosthesis should be encouraged.
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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 | 0.001 |
| 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 | 0.000 |
| 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".