Evaluation of contralateral arterial flow compensation using transcranial Doppler in acute internal carotid artery occlusion and implications for neurological outcome
Bibliographic record
Abstract
Acute internal carotid artery occlusion (AICAO) can result in malignant cerebral edema and unfavorable patient outcomes. This study evaluated the utility of transcranial Doppler (TCD) in assessing contralateral flow compensation and predicting outcomes in patients with AICAO. We enrolled 51 patients within 6 h of symptom onset and conducted TCD examinations to evaluate collateral circulation. Among the 51 patients, 40 (78.4%) had collateral flow. TCD showed excellent agreement with magnetic resonance angiography (MRA)/CT angiography (CTA) in assessing anterior communicating artery (ACoA) status (kappa = 0.873, p < 0.001). Our findings indicated that the absence of collaterals (OR = 7.649, p = 0.032), younger age (OR = 0.907, p = 0.048), and lower Alberta Stroke Program Early CT Score 24 h after onset (ASPECTs1) (OR = 0.276, p = 0.025) were independent predictors of malignant cerebral edema. Additionally, advanced age, elevated National Institutes of Health Stroke Scale Score (NIHSSs) in the Emergency Department, sole extracranial-to-intracranial collateral circulation (EICC), and absence ACoA were independently associated with worse outcomes (all p < 0.05). In conclusion, TCD evaluation of collateral circulation in AICAO patients can effectively predict the risk of malignant cerebral edema, with ACoA presence correlating with favorable outcomes and sole EICC linked to poorer prognosis. While age, NIHSSs and ASPECTs also contribute, TCD's assessment of collaterals provides key insights for patient management.
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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 | 0.003 |
| 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) | 0.000 | 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".