The Management of Intracranial Aneurysms: Current Trends and Future Directions
Bibliographic record
Abstract
Intracranial aneurysms represent a major global health burden. Rupture of an intracranial aneurysm is a catastrophic event. Without access to treatment, the fatality rate is 50% in the first 30 days. Over the last three decades, treatment approaches for intracranial aneurysms have changed dramatically. There have been improvements in the medical management of aneurysmal subarachnoid haemorrhage, and there has been an evolution of treatment strategies. Endovascular therapy is now the mainstay of the treatment of ruptured intracranial aneurysms based on robust randomised controlled trial data. There is now an expansion of treatment indications for unruptured intracranial aneurysms to prevent rupture with both microsurgical clipping and endovascular treatment. Both microsurgical and endovascular treatment modalities have evolved, in particular with the introduction of innovative endovascular treatment options including flow diversion and intra-saccular flow disruption. These novel therapies allow clinicians to treat more complex and previously untreatable aneurysms. We aim to review the evolution of treatment strategies for intracranial aneurysms over time, and discuss emerging technologies that could further improve treatment safety and functional outcomes for patients with an intracranial aneurysm.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".