Perfusion‐Based Relative Cerebral Blood Volume Is Associated With Functional Dependence in Large‐Vessel Occlusion Ischemic Stroke
Bibliographic record
Abstract
Background Pretreatment computed tomography perfusion parameter relative cerebral blood volume (rCBV) lesion volume has been shown to predict 90‐day modified Rankin Scale score in small‐core strokes with Alberta Stroke Program Early Computed Tomography Score ≥5, including those with medium‐vessel occlusions (mid and distal M2 segment occlusions). Hence, in this study we aim to assess the performance of different rCBV lesion volume thresholds (rCBV <42%, rCBV <38%, and rCBV <34%) with 90‐day modified Rankin Scale score including patients with large core (Alberta Stroke Program Early Computed Tomography Score <5) and strictly including only patients with anterior circulation large‐vessel occlusion. Methods and Results In this retrospective evaluation of our prospectively collected database, inclusion criteria were (1) Computed tomographic angiography confirmed anterior circulation large‐vessel occlusion from September 1, 2017, to October 1, 2023; and (2) diagnostic computed tomography perfusion. Student t test, Mann–Whitney U test, and χ 2 test were used in the univariate data analysis. Spearman's rank correlation analysis was used to assess correlations. Outcome measure was dichotomized into good functional outcome (90‐day modified Rankin Scale score, 0–2) and poor functional outcome (90‐day modified Rankin Scale score, 3–6) for logistic regression and receiver operating characteristic analysis. P ≤0.05 was considered significant. In total, 229 patients met our inclusion criteria. The majority of the patients (n=161) in our cohort had M1 occlusion. All the rCBV thresholds were significantly higher in patients with poor 90‐day functional outcomes and were independently associated with the outcome. Spearman's rank correlation analysis revealed a slightly stronger correlation of rCBV <42% (ρ=0.27, P <0.001), as compared with rCBV <38% (ρ=0.25, P <0.001) and rCBV <34% (ρ=0.24, P <0.001) with functional outcome. Receiver operating characteristic analysis revealed that rCBV <42% (area under the curve, 0.67 [95% CI, 0.60–0.74]; P <0.001) performed marginally better than rCBV <38% (area under the curve, 0.66 [95% CI, 0.59–0.73]; P <0.001), and rCBV <34% (area under the curve, 0.65 [95% CI, 0.58–0.72]; P <0.001). Conclusions All the rCBV thresholds were independently associated with poor 90‐day functional outcome; however, the rCBV <42% marginally outperformed rCBV <38% and rCBV <34% lesion volumes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".