Corticosteroid-induced spinal epidural lipomatosis in the pediatric age group: report of a new case and updated analysis of the literature
Bibliographic record
Abstract
Spinal epidural lipomatosis is a rare complication of chronic corticosteroid treatment. We report a new pediatric case and an analysis of this and 19 pediatric cases identified in the international literature. The youngest of these combined 20 patients was 5 years old when lipomatosis was diagnosed. Lipomatosis manifested after a mean of 1.3 (+/- 1.5) years (SD) (median, 0.8 years; range, 3 weeks - 6.5 years) of corticosteroid treatment. The corticosteroid dose at the time of presentation of the lipomatosis ranged widely, between 5 and 80 mg of prednisone/day. Back pain was the most common presenting symptom. Imaging revealed that lipomatosis almost always involved the thoracic spine, extending into the lumbosacral region in a subset of patients. Predominantly lumbosacral involvement was documented in only two cases. Although a neurological deficit at presentation was documented in about half of the cases, surgical decompression was not performed in the cases reported after 1996. Instead, reducing the corticosteroid dose (sometimes combined with dietary restriction to mobilize fat) sufficed to induce remission. In summary, pediatric spinal epidural lipomatosis remains a potentially serious untoward effect of corticosteroid treatment, which, if recognized in a timely manner, can have a good outcome with conservative treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".