Abstract 159: Posterior Communicating Artery Flow Diversion in Middle Cerebral Artery Stroke: Angiographic Evidence from IMS III
Bibliographic record
Abstract
Background: Only 20% of adults have a “fetal” posterior communicating artery (PCOMM) with carotid flow to the posterior cerebral artery. Dynamic pressure changes at the circle of Willis due to proximal artery occlusion may restore such collateral blood flow patterns. We investigated the findings and implications of PCOMM blood flow in middle cerebral artery (MCA) stroke at angiography in IMS III. Methods: The angiography core lab prospectively evaluated PCOMM blood flow and collateral circulation in proximal MCA or M1 occlusion. Proximal or distal M1 occlusion was noted with PCOMM flow scored (0-2) on ipsilateral carotid injections before and after endovascular therapy, correlating PCOMM status with ASITN/SIR leptomeningeal collateral grade, TICI reperfusion and subsequent clinical outcomes. Results: 122 patients with M1 occlusion at angiography (60 proximal, 62 distal) had peri-procedural evaluation of PCOMM status and associated collateral grade. Ipsilateral carotid injections revealed PCOMM flow diversion in 87/122 (71%) prior to revascularization, including 41/60 (68%) in proximal M1 and 46/62 (74%) in distal M1 (p=0.61) occlusions. After treatment, PCOMM patency was noted in 86/122 (71%), with 40/60 (67%) in proximal M1 and 46/62 (74%) in distal M1 (p=0.48) occlusions. Decrease in PCOMM score after therapy was noted in 11/122 (9%); 9/11 (82%) had mTICI 2B-3 reperfusion compared to 48/111 (43%) mTICI 2B-3 reperfusion in those with PCOMM unchanged (p=0.03). PCOMM flow (n=85) was associated with worse ASITN/SIR collaterals (median 2, IQR 2-3) than those without (n=29; median 3, IQR 2-3), p=0.09. PCOMM patency before treatment had 90-day mRS median of 4 (2-6) versus 3 (1-4), p=0.37. Conclusions: PCOMM flow diversion is common in MCA stroke, revealing an inverse correlation with leptomeningeal collaterals and dynamic changes following reperfusion.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".