The Association of Cerebral Blood Flow Measured Using Extracranial Carotid Ultrasound with Functional Outcomes in Patients with Anterior Circulation Large Vessel Occlusion After Endovascular Thrombectomy—A Retrospective Study
Bibliographic record
Abstract
Background: Endovascular mechanical thrombectomy (EVT) is regarded as the standard treatment for acute ischemic stroke with large vessel occlusion. Few studies have examined the evolution of cerebral flow after the acute stage of ischemic stroke. In this study, we examined the association of functional outcomes with cerebral blood flow by extracranial carotid sonography during the subacute phase after EVT and multiple prognostic variables. Methods: We conducted a single-center, retrospective, observational study between January 2018 and June 2023. Patients with acute stroke resulting from anterior circulation large vessel occlusion who underwent EVT were included. All patients underwent carotid sonography in the second week after EVT. Patients with fair (modified Rankin Scale [mRS]: 0–3) and poor outcomes (mRS: 4–6) were compared to determine the association between and identify the predictors of these factors and functional outcomes. Results: A total of 89 patients were included (female: 38 (42.7%); mean age: 69.45 ± 13.59 years). Multivariable logistic regression analysis revealed that three factors were independent predictors of fair outcomes: (1) the Alberta Stroke Program Early CT Score (odds ratio [OR]: 1.79; 95% confidence interval [CI]: 1.16–2.78; p = 0.009); (2) Thrombolysis in Cerebral Infarction 2b to 3 (OR: 4.91; 95%CI: 1.10–21.89; p = 0.037); (3) the ratio of treatment-side blood flow between the internal carotid artery and common carotid artery (QTI/QTC, OR: 45.35; 95% CI: 1.11–1847.51; p = 0.04). Conclusions: The ratio of QTI/QTC is a clinically relevant parameter as a potential predictor of favorable outcomes. This parameter can be used to formulate patient prognostic scores and help clinicians determine whether adequate cerebral perfusion is maintained during the subacute phase.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".