Brown-Sèquard Syndrome Produced by C3–C4 Cervical Disc Herniation
Bibliographic record
Abstract
STUDY DESIGN: The article presents a case in which Brown-Sèquard syndrome resulted from a painless C3-C4 disc herniation. OBJECTIVE: To raise spinal surgeons' awareness of this unusual clinical problem. SUMMARY OF BACKGROUND DATA: Brown-Sèquard syndrome involves ipsilateral loss of motor function combined with contralateral loss of pain and temperature sensation. Brown-Sèquard syndrome is commonly seen in the setting of spinal trauma or an extramedullary spinal neoplasm, but rarely it can be caused by a herniated cervical disc. METHODS: A 46-year-old man presented with progressive numbness and weakness in the left arm, mild neck pain, and reduced temperature sensation on the right side of the body. There was weakness in left arm and leg and proximal right lower limb. Magnetic resonance imaging showed large C3-C4 disc herniation compressing the spinal cord at that level. Anterior cervical discectomy and fusion with iliac crest bone graft was performed. RESULTS: Follow-up showed complete resolution of the neck pain, normal sensory function, and complete recovery of motor power in the left upper and right lower limb. There was a slight residual weakness in the left leg. CONCLUSION: Brown-Sèquard syndrome is rarely caused by a cervical disc herniation. This etiology may be underdiagnosed but has a more favorable outcome in those cases where rapid diagnosis is followed by spinal cord decompression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".