Clipping Could Be the Best Treatment Modality for Recurring Anterior Communicating Artery Aneurysms Treated Endovascularly
Bibliographic record
Abstract
BACKGROUND: The anterior communicating artery (AcoA) is the most common location for intracranial aneurysms. OBJECTIVE: To present occlusion outcomes, complication rate, recurrence rate, and predictors of recurrence in a large cohort with AcoA aneurysms treated primarily with endosaccular embolization. We also attempt to present data on the most effective treatment modality for recurrent AcoA aneurysms. METHODS: This is a retrospective, single-center study, reviewing the outcomes of 463 AcoA aneurysms treated endovascularly between 2003 and 2018. RESULTS: The study cohort consisted of 463 patients. Adequate immediate occlusion was achieved in 418 (90.3%). Independent functional status at discharge was observed in 269 patients (58.0%), and the mortality rate was 6.8% (31). At 6 months, adequate occlusion was achieved in 418 (90.4%). Of all the patients, recurrence was observed in 101 cases (21.8%), and of those, 98 (22.4%) underwent retreatment. The combined frequency of retreatment for the coiling group was 42.4%, which was significantly higher than the 0 incident of retreatment in the clipping group (P < .0001). Among the retreatment cohort, there was a significantly higher subsequent retreatment rate in the endovascular group (0% in the clipping group vs 42.4% in the endovascular group, P < .0001). CONCLUSION: Coiling with and without stent/balloon assistance is a relatively safe and effective modality for the treatment of AcoA aneurysms; however, in the setting of recurrence, microsurgical reconstruction leads to improved outcomes regarding durable occlusion, thus avoiding the potential for multiple interventions in the future.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".