Angiographic collateral venous phase: a novel landmark for leptomeningeal collaterals evaluation in acute ischemic stroke
Bibliographic record
Abstract
BACKGROUND: Although recanalization rates constantly increase (>80%), a favorable clinical outcome is achieved in only 45-55% of patients undergoing mechanical thrombectomy (MT) for anterior circulation stroke. Collateral circulation seems to play a major role in determining this discrepancy. The aim of the study was to investigate a novel angiographic landmark assessing the collateral venous phase (CVP) compared with the American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) score, based on the arterial collateral assessment. METHODS: Two hundred patients with anterior circulation stroke treated by MT between 2016 and 2021 were included. The ASITN/SIR score and the presence of CVP were blindly evaluated by expert neuroradiologists. Three subanalyses were performed comparing patients with good versus poor collaterals, CVP presence versus absence, and a composite analysis including both ASITN/SIR and CVP grading results. RESULTS: Good collateral circulation (ASITN >2) was observed in 113 patients (56.5%) whereas CVP was present in 90 patients (45%) and mostly in patients with good collaterals. Favorable clinical and neuroradiological outcomes were more likely observed in patients with both good collaterals and the presence of CVP than in those with good collaterals and absence of CVP (modified Rankin Scale score 0-2: 77.3% vs 7.9%, p<0.0001; mortality: 9.3% vs 26.3%, p=0.02; 24-hour Alberta Stroke Program Early CT Score: 8 vs 6, p<0.0001), while ASITN/SIR score alone was not significantly associated with clinical outcomes. CONCLUSIONS: The presence of CVP improves the angiographic assessment of collateral circulation. CVP could be proposed as a new imaging landmark to better understand the functionality of collaterals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".