Abstract T MP6: Angiographic Arteriovenous Shunting in Large Vessel Occlusion Strokes: Not an Ominous Sign
Bibliographic record
Abstract
Background: The angiographic visualization of arteriovenous shunting (AVS) in large vessel occlusion strokes (LVOS) is thought to be a consequence of microcirculatory collapse in the setting of irreversible tissue injury and therefore may represent an ominous prognostic sign. We sought to establish the relationship between the presence of AVS on CT imaging characteristics and clinical outcomes in the Solitaire Flow Restoration Thrombectomy for Acute Revascularization (STAR) trial. Methods: STAR Trial patients with complete angiographic images were categorized according to the presence (AVS+) or absence (AVS-) of AVS at the end of the thrombectomy procedure. Baseline variables were compared to assess for any significant differences amongst the two groups. The impact of AVS on pre- and post-treatment CT imaging and in the rates of revascularization (TICI 2b-3), symptomatic intracranial hemorrhage (sICH), good functional outcomes (90-day mRS≤2), and 90-day mortality was subsequently analyzed. Results: There was no significant differences in terms of age, baseline NIHSS, gender, time to treatment, or glucose levels between the AVS+ (n=52) and the AVS- (n=116) patients (Table 1). AVS+ patients had a non-significant trend towards more proximal occlusions. The presence of AVS did not have any significant impact on the rates of favorable CT imaging on either pre-treatment (AVS- vs. AVS+ ASPECTS>7: 65.5 vs. 72%;p=0.47) or post-treatment (ASPECTS>7:45.6 vs. 51%;p=0.61) scans. Similarly, AVS was not associated with any significant differences in the rates of good outcome (58.6 vs. 65.4%;p=0.49), mortality (8.6 vs. 3.8%;p=0.35), sICH (1.7 vs. 1.9%;p=0.92), or recanalization (89.7 vs. 92.3%;p=0.78). Conclusions: In contrast to the current belief, the angiographic visualization of AVS in LVOS patients does not appear to have any meaningful consequences in terms of infarct size or clinical outcomes and therefore should not influence treatment decisions.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".