P.205 Association Between Vein of Galen Aneurysmal Malformation and Hirayama Disease: A Clue into Pathophysiology?
Bibliographic record
Abstract
Background: Hirayama Disease (HD) is a rare disorder consisting of insidious onset of unilateral weakness and atrophy of the forearm and intrinsic hand muscles. Vein of Galen aneurysmal malformations (VGAMs) are rare congenital cerebral vascular malformations, consisting of high-flow arteriovenous shunting between a persistent median prosencephalic vein and arterial feeders. Methods: 14 years old boy known for VGAM presented with left-sided HD. His cervical MRI revealed enlarged epidural with anterior, left-ward displacement of the posterior dura and spinal cord. He underwent surgical treatment by laminotomies, along with tenting of an autologous duroplasty to the overlying laminae. Results: We decided to combine epidural venous plexus coagulation with posterior duraplasty and dural fixation using tenting suture which led to a favorable clinical outcome has not been previously proposed in the literature. We hypothesize that in this context, an abnormal vasculature could also predispose to posterior epidural venous plexus engorgement, anterior dural displacement in cervical flexion, and microvascular changes in the anterior spinal arterial circulation, leading to the progressive anterior horn cell ischemia that lead to the clinical phenotype of HD. Conclusions: The association between HD and VGAM in this patient may provide clues with regard to the pathophysiology of HD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".