Decreased Quantitative Cerebral Blood Volume Is Associated With Poor Outcomes in Large Core Patients
Bibliographic record
Abstract
BACKGROUND: Recent large core trials have highlighted the effectiveness of mechanical thrombectomy (MT) in acute ischemic stroke with large vessel occlusion. Variable perfusion-imaging thresholds and poor Alberta Stroke Program Early Computed Tomography Score reliability underline the need for more standardized, quantitative ischemia measures for MT patient selection. We aimed to identify the computed tomography perfusion parameter most strongly associated with poor outcomes in patients with acute ischemic stroke-large vessel occlusion with significant ischemic cores. METHODS: In this study from 2 comprehensive stroke centers from 2 comprehensive stroke centers within the Johns Hopkins Medical Enterprise (Johns Hopkins Hospita-East Baltimore and Bayview Medical Campus) from July 29, 2019 to January 29, 2023 in a continuously maintained database, we included patients with acute ischemic stroke-large vessel occlusion with ischemic core volumes defined as relative cerebral blood flow <30% and ≥50 mL on computed tomography perfusion or Alberta Stroke Program Early Computed Tomography Score <6. We used receiver operating characteristics to find the optimal cutoff for parameters like cerebral blood volume (CBV) <34%, 38%, 42%, and relative cerebral blood flow >20%, 30%, 34%, 38%, and time-to-maximum >4, 6, 8, and 10 seconds. The primary outcome was unfavorable outcomes (90-day modified Rankin Scale score 4-6). Multivariable models were adjusted for age, sex, diabetes, baseline National Institutes of Health Stroke Scale, intravenous thrombolysis, and MT. RESULTS: We identified 59 patients with large ischemic cores. A receiver operating characteristic curve analysis showed that CBV<42% ≥68 mL is associated with unfavorable outcomes (90-day modified Rankin Scale score 4-6) with an area under the curve of 0.90 (95% CI, 0.82-0.99) in the total and MT-only cohorts. Dichotomizing at this CBV threshold, patients in the ≥68 mL group exhibited significantly higher relative cerebral blood flow, time-to-maximum >8 and 10 seconds volumes, higher CBV volumes, higher HIR, and lower CBV index. The multivariable model incorporating CBV<42% ≥68 mL predicted poor outcomes robustly in both cohorts (area under the curve for MT-only subgroup was 0.87 [95% CI, 0.75-1.00]). CONCLUSIONS: CBV<42% ≥68 mL most effectively forecasts poor outcomes in patients with large-core stroke, confirming its value alongside other parameters like time-to-maximum in managing acute ischemic stroke-large vessel occlusion.
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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 | 0.001 |
| 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".