Long-Term Hemorrhage and Reperfusion Rates of Coiled Aneurysms: A Single-Center Experience
Bibliographic record
Abstract
Background: The endovascular approach has emerged as standard therapy for many intracranial aneurysms (IAs) to prevent hemorrhage, yet its long-term durability varies considerably. The aim of this study was to evaluate the safety and effectiveness of an initially deliberate endovascular approach regarding IA hemorrhage rates over a long-term follow-up period. Methods: This retrospective single-center study included all consecutive patients with endovascularly treated IAs who presented between January 2008 and December 2020 with a follow-up of at least 12 months. The primary endpoint was the proportion of patients with long-term IA hemorrhage rates and reperfusion. The secondary endpoint was treatment-related morbidity and mortality. Independent risk factors for IA reperfusion over the long term were analyzed using multivariate logistic regression. Results: Endovascular treatment was the therapy of choice for 333 patients with IAs, among whom 188 (57%) experienced rupture upon presentation. Complete coiling (Raymond I) was noted in 162 (49%) of the patients, with primary supportive devices being used in 51 (15%) patients. After a median (±SD) follow-up time of 34 ± 41 months (range 12–265 months), IA reperfusion was noted in 158 (47%), necessitating retreatment in 105 (32%) of the patients. Over the long term, hemorrhage was noted in four (1%) patients. Multivariate analysis revealed aneurysmal multilobarity (HR 1.8, 95%CI 1.2–2.7; p = 0.004) and a patient age of ≥50 years (HR 1.7, 95% CI 1.1–2.5, p = 0.01) as independent predictors of reperfusion over time. Intervention-related morbidity was noted in 16 (4.8%) patients, namely, thrombosis formation and contrast extravasation in 8 (2.4%) patients each, while no intervention-induced mortality was observed. Conclusion: In the long term, the hemorrhage rate in patients with IA with an initially more conservative endovascular approach is low. Therefore, a deliberate endovascular treatment approach might be justified.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".