Injectable Synthetic Beta-Tricalcium Phosphate/Calcium Sulfate (GeneX) for the Management of Contained Defects Following Curettage of Benign Bone Tumours
Bibliographic record
Abstract
Benign and low-grade malignant bone tumours are often treated with curettage and filling of the resultant defect using any of a number of materials, including autologous bone grafts, allografts, or synthetic materials. The objective of this study was to report our experience using a synthetic bone graft substitute in these patients. Ten consecutive cases (four males, six females; mean age, 36 years) of benign bone tumours were treated surgically at a tertiary musculoskeletal oncology centre, between 2019 and 2021. Following curettage, the contained defects were managed with injectable beta-tricalcium phosphate/calcium sulfate (GeneX; Biocomposites Ltd., Keele, UK). The desired outcomes were early restoration of function and radiographic evidence of healing. No other graft materials were used in any of the patients. The mean follow-up was 24 months (range, 20-30 months). All patients in this series (100%) demonstrated radiographic evidence of healing and resumed their daily living activities. There were no tumour recurrences and no complications were encountered with the use of GeneX. In patients with contained defects following curettage of benign bone tumours, we found GeneX to be a safe and effective filling agent. These findings contrast with some existing studies that have reported local complications with the use of injectable beta-tricalcium phosphate/calcium sulfate.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".