Poor Cortical Venous Opacification on Baseline Computed Tomography Angiography Predicts Parenchymal Hemorrhage After Thrombectomy
Bibliographic record
Abstract
Background Although the association between cortical venous opacification (VO) and clinical outcomes has been shown in previous studies, little is known about the relationship between parenchymal hemorrhage (PH) and VO in patients with acute stroke. We aimed to determine whether cortical VO assessed on computed tomography angiography correlates with the risk of PH following endovascular treatment. Methods This is a post hoc analysis of the ESCAPE NA‐1 (Efficacy and Safety of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke) trial. Control‐arm patients with adequate venous assessment on computed tomography angiography were included. Any PH and symptomatic intracranial hemorrhage were compared between patients with poor VO (cortical vein opacification score<3) versus good opacification (cortical vein opacification score≥3). The relationships with unfavorable functional outcome (90‐day modified Rankin scale 3–6) and 24‐hour infarct volume were assessed. Multivariable logistic and linear regressions were performed. Results Among the 545 patients that met the inclusion criteria, 55 (10.2%) had PH and 21 (3.9%) had symptomatic intracranial hemorrhage. Poor VO was observed in 286 (52.5%) patients (median age, 71 years; 51.4% women). PH was more frequent in the patients with poor VO compared with good VO: 43 of 283 (15.2%) versus 12 of 257 (4.7%) (adjusted odds ratio, 3.43; [95% CI, 1.66–7.10]). Symptomatic intracranial hemorrhage was not significantly higher in the poor versus good opacification groups: 14 of 283 (5.0%) versus 7 of 257 (2.7%). Poor opacification was a predictor of unfavorable functional outcome (adjusted odds ratio, 3.01; [95% CI, 1.95–4.64]; P <0.001), and larger final infarct volume (adjusted B 0.74; [95% CI, 0.45–1.03]; P <0.001). Conclusions Poor VO on computed tomography angiography is strongly associated with an increased risk of PH and worse clinical outcomes after endovascular treatment, and therefore it may be used as a tool for risk stratification in patients with stroke.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".