Flow Diversion for the Treatment of Basilar Apex Aneurysms
Bibliographic record
Abstract
BACKGROUND: Flow diversion for basilar apex aneurysms has rarely been reported. OBJECTIVE: To assess flow diversion for basilar apex aneurysms in a multicenter cohort. METHODS: Retrospective review of prospectively maintained databases at 8 academic institutions was performed from 2009 to 2016 to identify patients with basilar apex aneurysms treated with flow diversion. Clinical and radiographic data were analyzed. RESULTS: Sixteen consecutive patients (median age 54.5 yr) underwent 18 procedures to treat 16 basilar apex aneurysms with either the Pipeline Embolization Device (Medtronic Inc, Dublin, Ireland) or Flow Redirection Endoluminal Device (Microvention, Tustin, California). Five aneurysms (31.3%) were treated in the setting of subarachnoid hemorrhage. Seven aneurysms (43.8%) were treated with flow diversion alone, while 9 (56.2%) underwent flow diversion and adjunctive coiling. At a median follow-up of 6 mo, complete (100%) and near-complete (90%-99%) occlusion was noted in 11 (68.8%) aneurysms. Incomplete occlusion occurred more commonly in patients treated with flow diversion alone compared to those with adjunctive coiling. Patients with partial occlusion were significantly younger. Retreatment with an additional flow diverter and adjunctive coiling occurred in 2 aneurysms with wide necks. There was 1 mortality in a patient (6.3%) who experienced posterior cerebral artery and cerebellar strokes as well as subarachnoid hemorrhage after the placement of a flow diverter. Minor complications occurred in 2 patients (12.5%). CONCLUSION: Flow diversion for the treatment of basilar apex aneurysms results in acceptable occlusion rates in highly selected cases. Both primary flow diversion and rescue after failed clipping or coiling resulted in a modified Rankin Scale score that was either equal or better than at presentation and the technology represents a viable alternative or adjunctive option.
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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 | 0.003 |
| 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) | 0.001 | 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".