Venous outflow profiles are associated with early edema progression in ischemic stroke
Bibliographic record
Abstract
Background: In patients with acute ischemic stroke due to large vessel occlusion (AIS–LVO), development of extensive early ischemic brain edema is associated with poor functional outcomes, despite timely treatment. Robust cortical venous outflow (VO) profiles correlate with favorable tissue perfusion. We hypothesized that favorable VO profiles (VO+) correlate with a reduced early edema progression rate (EPR) and good functional outcomes. Methods: Multicenter, retrospective analysis to investigate AIS–LVO patients treated by mechanical thrombectomy between May 2013 and December 2020. Baseline computed tomography angiography (CTA) was used to determine VO using the cortical vein opacification score (COVES); VO+ was defined as COVES ⩾ 3 and unfavorable as COVES ⩽ 2. EPR was determined as the ratio of net water uptake (NWU) on baseline non-contrast CT and time from symptom onset to admission imaging. Multivariable regression analysis was performed to assess primary (EPR) and secondary outcome (good functional outcomes defined as 0–2 points on the modified Rankin scale). Results: A total of 728 patients were included. Primary outcome analysis showed VO+ (β: –0.03, SE: 0.009, p = 0.002), lower presentation National Institutes of Health Stroke Scale (NIHSS; β: 0.002, SE: 0.001, p = 0.002), and decreased time from onset to admission imaging (β: –0.00002, SE: 0.00004, p < 0.001) were independently associated with reduced EPR. VO+ also predicted good functional outcomes (odds ratio (OR): 5.07, 95% CI: 2.839–9.039, p < 0.001), while controlling for presentation NIHSS, time from onset to imaging, general vessel reperfusion, baseline Alberta Stroke Program Early CT Score, infarct core volume, EPR, and favorable arterial collaterals. Conclusions: Favorable VO profiles were associated with slower infarct edema progression and good long-term functional outcomes as well as better neurological status and ischemic brain alterations at admission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".