Cerebral blood volume index may be a predictor of independent outcome of thrombectomy in stroke patients with low ASPECTS
Bibliographic record
Abstract
INTRODUCTION: To evaluate the predictors for efficacy and safety of patients with acute ischemic stroke (AIS) and Alberta Stroke Program Early Computed Tomographic Score (ASPECTS) ＜6 undergoing endovascular therapy (EVT). METHODS: This study retrospectively analyzed consecutive patients presented between December 2020 and December 2021 with large vessel occlusions (LVO) within the anterior circulation and an ASPECTS ＜6, followed by EVT. The efficacy outcome was 90-day functional independence, defined as modified Rankin Scale (mRS) score 0-3. The primary safety outcome was symptomatic intracranial hemorrhage (sICH). Secondary safety outcomes included 90-day all-cause mortality and 24-hour any ICH. RESULTS: A total of 22 patients were included. The percentage of patients with mRS 0-3 at 90 days was 36.4% (8/22). The occurrence of sICH was 22.7% (5/22). The occurrence of any ICH was 45.5% (10/22). The 90-day all-cause mortality was 36.4% (8/22). Median (interquartile range, IQR) cerebral blood volume (CBV) index was 0.5 (0.4-0.7). CBV index in mRS 0-3 group (n = 8) was higher than mRS 4-5 group (n = 14) (P＜0.05). There was no significant difference of age, gender, comorbidities, baseline National Institutes of Health Stroke Scale (NIHSS) score, mismatch ratio, CBV index, interval between stroke onset and re-perfusion, good re-perfusion rate between sICH group (n = 5) and non-sICH group (n = 17). CONCLUSIONS: AIS patients with low ASPECTS can still benefit from EVT and gain good functional outcome, especial those had higher CBV index on pre-EVT computed tomography perfusion (CTP). Further studies with larger sample size are needed to validate our findings.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".