Impact of individual intracranial arterial aneurysm morphology on initial obliteration and recurrence rates of endovascular treatments: a multivariate analysis
Bibliographic record
Abstract
OBJECT: The goal was to investigate whether morphological features of aneurysms can be identified that determine initial success and recurrence rates of coiled aneurysms of the basilar artery tip, the posterior communicating artery (PCoA), and the anterior communicating artery. METHODS: The authors evaluated 202 aneurysms in connection with their pretreatment morphological features including size, neck-to-dome ratio, angulation of the aneurysm in relation to the parent artery, orientation of the aneurysm dome, and associated anatomical variations. The mean follow-up was 19 months (range 6-96 months) after endovascular coil occlusion. Using multivariate logistic regression, probabilities for initial complete occlusion and long-term stability of the treatment were calculated. RESULTS: Recanalization occurred in 49 of 202 cases. Favorable factors for long-term stability included small aneurysms with small necks. However, additional factors related to local hemodynamic forces could be identified for the different aneurysm locations, which may influence initial success rates and long-term stability of aneurysm treatment with endovascular coiling. These factors were a medial dome orientation and a symmetrical disposition of both A(1) segments (for the anterior communicating artery), a posteroinferior dome orientation and a small-size PCoA (for the PCoA), and a cranial symmetrical fusion (for the basilar artery tip). CONCLUSIONS: A detailed pretreatment analysis of morphological features of aneurysms may help to determine those aneurysms that are more prone to recurrence, which could add to the treatment decision and the follow-up algorithm.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".