Large vascular malformation in a child presenting with vascular steal phenomenon managed with pial synangiosis
Bibliographic record
Abstract
The management of large and giant arteriovenous malformations (AVMs) in patients presenting with nonhemorrhagic neurological deficits secondary to vascular steal phenomenon is challenging and controversial. In many cases, large AVMs cannot be completely excised or cured, leaving patients with residual or partially treated AVMs, the natural history of which is unknown. Additionally, large, diffuse vascular malformations with multiple, small feeders, slow flow, or so-called cerebral proliferative angiopathy represent a related but distinct clinical and angiographic entity that may require a different therapeutic approach than traditional brain AVMs. The current management of children with other conditions of chronic cerebral hypoperfusion, such as moyamoya disease, involves consideration of surgical revascularization to enhance blood flow to the compromised hemisphere. Here, the authors present the case of a young child with a large thalamic vascular malformation who presented with clinical and radiological features of vascular steal and ischemia. In an effort to augment flow to the hypoperfused brain and protect against future ischemia, the authors treated the child with unilateral pial synangiosis. At 12 months, postoperative angiography demonstrated robust neovascularization, and the child has not sustained any further ischemic events. The authors discuss concept of vascular malformation-related hypoperfusion and the utility of indirect revascularization for inoperable vascular malformations presenting with ischemic symptoms.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".