DEXA as a Predictor of Fixator Removal in Distraction Osteogenesis
Bibliographic record
Abstract
UNLABELLED: Premature removal of the fixator after a lengthening procedure can result in gradual bending or acute fracture of the regenerate. We reviewed the records of 26 patients who underwent 28 limb lengthenings between 1997 and 2005 to assess the post lengthening regenerate fracture rate and bone healing index when using dual energy xray absorptiometry (DEXA) to aid in deciding on when to remove the fixator. Sixteen male and 10 female patients with an average age at lengthening of 12.3 years underwent an average lengthening of 5.2 cm (range, 3-9.1 cm). Nineteen femurs and nine tibiae were lengthened. Serial monthly DEXA scans were analyzed for bone mineral density. Bone healing indices and post fixator removal complications were assessed. The fixators were removed once the bone mineral density had plateaued to a less than 10% increase and plain radiographs showed no obvious defects precluding fixator removal. There were no regenerate fractures and only one fracture in the proximal segment of the lengthened bone after apparatus removal and the healing index for the series averaged 47 d/cm (range, 20-73 d/cm). Using serial DEXA scans during the consolidation phase of lengthening has a low rate (3.6%) of fractures while maintaining an acceptable bone healing index without excessively increasing fixation time. LEVEL OF EVIDENCE: Level IV, therapeutic retrospective study. See the Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.002 | 0.010 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".