O19 Treatment of unruptured distal anterior cerebral artery aneurysms with flow-diverter stents: a large multi-center experience
Bibliographic record
Abstract
Introduction Evidence about the safety and the efficacy of flow diversion for distal anterior cerebral artery (DACAs) -beyond the anterior communicating artery (AComA)- aneurysms is very poor. Aim of Study We present the largest multicentric analysis evaluating the outcomes of flow diverters in unruptured DACAs aneurysm treatment. Methods Databases from 37 centers were retrospectively reviewed for unruptured DACAs aneurysms treated with flow diverters. Demographics, clinical presentation, radiographic characteristics, procedural complications, and outcomes were assessed. The occlusion of the aneurysm was assessed using the O’Kelly-Marotta (OKM) scale. Results A total of 168 patients with an unruptured DACAs aneurysm were treated between January 2018 and December 2022. One hundred twenty-five were women (74.4%) and median age was 61 (IQR 52-67) years. The most common morphology was saccular (88.7%), with a branch involvement in 61,9% of cases. Median vessel diameter was 1.9 mm, and the FD was successfully deployed in 99,4 of cases. 96,4% required a single FD, while in 3,6% of cases 2 FDs were implanted. Median imaging follow-up was 16,5 (IQR 7-24) months. At last follow-up the rate of occlusion (OKM C+D,) was 82.1%. Symptomatic thrombo-embolic or hemorrhagic complications occurred in 5.3%. The rate of retreatment was 1,2%. Mortality 0.6%. Conclusion Our study findings indicate that flow diverters represent a beneficial treatment option for DACAs aneurysms. Follow-up assessments revealed favorable aneurysm occlusion rates alongside a favorable safety profile. Disclosure of Interest no.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".