Asymptomatic unruptured intracranial aneurysms: approach to screening and treatment.
Bibliographic record
Abstract
ABSTRACTOBJECTIVETo review the current knowledge of screening and treatment of asymptomatic unruptured intracranial aneurysms (AUIAs) using a case-based approach.SOURCES OF INFORMATIONPubMed was searched from January 1995 to January 2008 using the phrase unruptured intracranial aneurysm. Scientific statements of the Stroke Council of the American Heart Association pertaining to intracranial aneurysms were also reviewed.MAIN MESSAGEMost small AUIAs (</= 5 mm) do not rupture, and the risks of treatment are substantial. Most small AUIAs can therefore be managed conservatively. Endovascular coiling or surgical clipping of larger aneurysms (> 5 mm) should be considered on a case-by-case basis.CONCLUSIONThere is currently a lack of sound scientific evidence to support treatment of unruptured intracranial aneurysms. A prospective randomized controlled trial-Trial on Endovascular Aneurysm Management-is now under way to address this issue. It is expected to conclude in 2021.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".