An Aneurysmal Bone Cyst in the Cervical Spine of a 10-Year-Old Girl: A Case Report
Bibliographic record
Abstract
STUDY DESIGN: An aneurysmal bone cyst in the neural arch of the fourth cervical vertebra of a 10-year-old girl is reported, along with a brief review of the literature on the topic. OBJECTIVE: To report the presentation and diagnosis of this disorder along with a discussion of the major pitfalls of treatment. SUMMARY OF BACKGROUND DATA: An aneurysmal bone cyst occurs commonly in the second decade, with a predilection for the lumbar spine. With occurrence in the neural arch of a cervical vertebra, the potential for instability following surgical excision is high. METHODS: A 10-year-old white female presented with neck pain of 3 months' duration. Diagnostic imaging revealed an expansile lytic lesion in the spinous process and lamina of the fourth cervical vertebra. Surgical treatment consisted of excisional biopsy and a segmental instrumented posterior fusion from C3-C5. The histopathology was consistent with an aneurysmal bone cyst. RESULTS: Surgical excision consisting of laminectomy and instrumented segmental fusion provided a good clinical result, and minimized the risk and degree of the 2 most common complications: recurrence of the tumor; and postlaminectomy kyphosis, a frequent occurrence in the pediatric population. CONCLUSIONS: In pediatric patients who develop a bone tumor of the posterior elements of the cervical spine, careful clinical and radiologic evaluation is necessary to narrow the differential diagnosis. In most cases, a complete excision should be performed if possible. The risk of postlaminectomy kyphosis is high in the pediatric age population. As such, a fusion should be considered whenever a laminectomy is performed in the immature cervical spine. Risk factors for kyphosis include a high cervical level, multiple laminectomy levels, and postoperative irradiation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| 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".