Emergency Noninvasive Angiography for Acute Intracerebral Hemorrhage
Bibliographic record
Abstract
Spontaneous ICH is a devastating condition and is associated with significant mortality in the acute phase due to ongoing hemorrhage and hematoma expansion. A growing body of evidence suggests that there may be considerable utility in performing noninvasive vascular imaging during the acute-to-early phase of ICH. CTA has become widely available and is sensitive and specific for detecting vascular causes of secondary ICH such as aneurysms, arteriovenous malformations, dural arteriovenous fistulas, intracranial dissections, and neoplasm. CT venography can also diagnose dural sinus thrombosis presenting as hemorrhagic infarction. Recent data from stroke populations demonstrate a relatively low risk to patients when contrast is administered in the absence of a known serum creatinine. Detection of acute contrast extravasation within the hematoma ("spot sign") with CT angiography is predictive of subsequent hematoma expansion and is associated with increased morbidity and mortality. Risk stratification based on acute CTA can inform and expedite decision-making regarding intensive care unit admission, blood pressure control, correction of coagulopathy, and neurosurgical consultation. Noninvasive vascular imaging should be considered as an important component of the initial diagnostic work-up for patients presenting with acute ICH.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".