Rapidly Deteriorating Degenerative Cervical Myelopathy Following Ventricular Shunt Revision for Hydrocephalus: Case Report
Bibliographic record
Abstract
A female patient in her early 40s presented with a several-month history of gait unsteadiness and dragging her left leg. She had a background of congenital hydrocephalus, treated with a ventriculoatrial shunt. On examination, she had increased tone and brisk reflexes in the lower limbs and a positive Hoffmann sign. A computed tomography (CT) scan and shunt series x-rays identified hydrocephalus secondary to a disconnected shunt. Magnetic resonance imaging (MRI) of her cervical spine was also performed as part of the workup for her presenting symptoms and demonstrated features compatible with degenerative cervical myelopathy (DCM). The patient subsequently underwent a shunt revision. Following the operation, her walking and hand function deteriorated over a period of several weeks. She consequently underwent an anterior cervical decompression and fusion for DCM, which partially improved her symptoms. The sequence of events suggests that the shunt surgery may have precipitated a worsening of the DCM. Possible explanations include spinal cord injury related to neck extension or hypoperfusion during intubation and general anesthesia or the loss of cerebrospinal fluid cushioning following the reinstitution of effective cerebrospinal fluid shunting. Surgeons should be alert to this possibility and offer prompt surgical intervention for DCM if required.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 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".