Preliminary study of transcranial Doppler observation of cerebral herniation in acute internal carotid artery occlusion
Bibliographic record
Abstract
Abstract Background and Purpose The purpose of this study was to attempt early detection of the risk of cerebral herniation after acute internal carotid artery occlusion (AICAO) using transcranial Doppler. Methods Twenty-four patients were enrolled within 6 hours of symptom onset. All patients underwent transcranial Doppler (TCD), head computed tomography (CT), magnetic resonance angiography (MRA) or computed tomography angiography (CTA). The National Institutes of Health Stroke Scale (NIHSS) score and the Alberta Stroke Program Early CT Score (ASPECTS) were performed in emergency department and 24 hours after the onset of acute ischemic stroke (AIS) (designated as NIHSS1 and ASPECTS1, respectively). TCD to determine collateral circulation was performed immediately after patient admission. Results Sex, risk factors, hemisphere, intravenous recombinant tissue plasminogen activator (rt-PA), and time from onset of symptoms to initiation treatment showed no difference between patients with or without cerebral herniation. The age of the group with cerebral hernia was significantly younger than that of the group without cerebral hernia (P=0.000). Assessment of the anterior communicating artery (ACoA) by TCD was in high agreement with assessment by MRA or CTA (kappa=0.625, P=0.002). Correlation analysis showed that the likelihood of a cerebral herniation event was positively correlated with absence of a communicating artery (r n =0.660, P=0.002) and negatively correlated with ACoA (r n =0.513, P=0.003) and ASPECTS1 (r s =0.528, P=0.008), but was not correlated with NIHSS score, NIHSS1 score, △NIHSS (NIHSS1-NIHSS), admission awareness, and stroke volume (P > 0.05). Conclusions TCD assessment of collateral status could more rapidly indicate the risk of cerebral herniation. Lack of collateral flow may predict the occurrence of cerebral hernia. Compensation of ACoA may indicate a lower risk of cerebral hernia.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".