Spinal Hemorrhage Leading to Cerebral Vasospasm and Infarction
Bibliographic record
Abstract
Only one case of intracranial arterial vasospasm resulting cerebral infarction was previously described in the setting of spinal hemorrhage. The speculation of such symptomatic vasospasm being caused by an intracranial extension of the spinal hemorrhage has been unproven. Here we describe two patients with extensive spinal hemorrhage demonstrated on spinal magnetic resonance imaging (MRI). During their subsequent course, both patients developed cranial signs that included encephalopathy, visual deficit and aphasia. In both cases, small amount of intracranial hemorrhage was detected on head imaging, representing an extension of the spinal hemorrhage. Multiple areas of acute ischemia were seen on brain MRI in both patients. On digital subtraction angiography, diffuse vasospasm of carotid and vertebrobasilar arteries was seen which became normalized prior to discharge. Our report suggests that in treating patients with spinal hemorrhage, physicians need to be aware of possible intracranial hemorrhagic extension and subsequent cerebral vasospasm leading to ischemia. As symptoms of intracranial origin are commonly seen in patients with spinal hemorrhage, the incidence of cerebral vasospasm in this setting could be underestimated. doi: http://dx.doi.org/10.4021/jnr119w
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".