Scintigraphic Evaluation of the Stump Region After Extremity Amputation and the Effect of Scintigraphy on Treatment
Bibliographic record
Abstract
BACKGROUND: We evaluated the stump region with scintigraphy and compared the correlation of treatment modalities and scintigraphic results. METHODS: Sixty-eight cases with extremity amputation were included in the study. Amputation applied cases underwent four-phase Tc-99m hydroxymethylene diphosphonate scintigraphy. Groups were performed according to the scanning time after amputation and amputation regions. After scintigraphic evaluation, results were recorded into five groups: osteomyelitis, soft-tissue infection, reactive changes secondary to surgery, chronic osteomyelitis, and normal. Post-surgical treatment modalities of the patients were determined and compared with scintigraphic results. RESULTS: In the scintigraphic evaluation of stump regions of the 68 amputated cases, 34 patients had acute osteomyelitis, one had chronic osteomyelitis, 16 had soft-tissue infection, and eight had changes secondary to the surgery. Nine of 68 cases had normal scintigraphic features. In the scintigraphic evaluation, 43 patients took antibiotic treatment and 16 had surgery. There was a strong correlation between scintigraphic results and treatment approach (P < 0.0001, r = 0.803) by means of preferred therapy and effectiveness of the therapy according to the scintigraphic results. Scintigraphy need increases with age after amputation and a negative correlation between patient age and scintigraphic need was found (P < 0.02, r = -0.339). There was no pathology in the follow-up in the cases that were scintigraphically normal. CONCLUSION: Bone scintigraphy is a cost-effective, non-invasive, and efficient method that directs treatment in the evaluation of the stump region after amputation.
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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 | 0.000 |
| 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".