Spontaneous resolution of idiopathic thoracic spinal cord herniation: case report
Bibliographic record
Abstract
Spinal cord herniation is a relatively rare but increasingly recognized clinical entity, with fewer than 200 cases reported in the literature to date. The etiology of this condition remains unknown, and surgery is used as the primary treatment to correct the herniation and consequent spinal cord compromise. Some patients without clinical progression have been treated with nonoperative measures, including careful follow-up and symptomatic physical therapy. To date, however, there has been no published report on the resolution of spinal cord herniation without surgical intervention. The patient in the featured case is a 58-year-old man who presented with mild thoracic myelopathy and imaging findings consistent with idiopathic spinal cord herniation. Surprisingly, updated MRI studies, obtained to better delineate the pathology, showed spontaneous resolution of the herniation. Subsequent MRI 6 months later revealed continued resolution of the previous spinal cord herniation. This is the first report of spontaneous resolution of a spinal cord herniation in the literature. At present, the treatment of this disorder is individualized, with microsurgical correction used in patients with progressive neurological impairment. The featured case highlights the potential variability in the natural history of this condition and supports considering an initial trial of nonoperative management for patients with mild, nonprogressive neurological deficits.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| 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".