A2, M2, P2 aneurysms and beyond: results of treatment with pipeline embolization device in 65 patients
Bibliographic record
Abstract
BACKGROUND: Intracranial aneurysms located in the distal vessels are rare and remain a challenge to treat through surgical or endovascular interventions. OBJECTIVE: To describe a multicenter approach with flow diversion using the pipeline embolization device (PED) for treatment of distal intracranial aneurysms. METHODS: Cases of distal intracranial aneurysms defined as starting on or beyond the A2 anterior cerebral artery, M2 middle cerebral artery, and P2 posterior cerebral artery segments were included in the final analysis. RESULTS: 65 patients with distal aneurysms treated with the PED were analyzed. Median aneurysm size at the largest diameter was 7.0 mm, 60% were of a saccular morphology, and 9/65 (13.8%) patients presented in the setting of acute rupture. Angiographic follow-up data were available for 53 patients, with a median follow-up time of 6 months: 44/53 (83%) aneurysms showed complete obliteration, 7/53 (13.2%) showed reduced filling, and 2/53 (3%) showed persistent filling. There was no association between patient characteristics, including aneurysm size (P=0.36), parent vessel diameter (P=0.27), location (P=0.81), morphology (P=0.63), ruptured status on admission (P=0.57), or evidence of angiographic occlusion at the end of the embolization procedure (P=0.49). Clinical outcome data were available for 60/65 patients: 95% (57/60) had good clinical outcome (modified Rankin Scale score of 0-2) at 3 months. CONCLUSIONS: This large multicenter study of patients with A2, M2, and P2 distal aneurysms treated with the PED showed that flow diversion may be an effective treatment approach for this rare type of vascular pathology. The procedural compilation rate of 7.7% indicates the need for further studies as the flow diversion technology constantly evolves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".