Unruptured Intracranial Aneurysms
Bibliographic record
Abstract
SUMMARY: The preventive treatment of unruptured aneurysms has been performed for decades despite the lack of evidence of a clinical benefit. Reports of observational studies such as the International Study of Unruptured Intracranial Aneurysms (ISUIA) suggest that preventive treatments are rarely justified. Are these reports compelling enough to guide clinical practice? The ISUIA methods and data are reviewed and analysed in a more conventional manner. The design of the appropriate clinical research program is approached by steps, reviewing potential problems, from the formulation of the precise research question to the interpretation of subgroup analyses, including sample size, representativity, duration of observation period, blinding, definition of outcome events, analysis of cross-overs, losses to follow-up, and data reporting. Unruptured intracranial aneurysms observed in ISUIA ruptured at a minimal annual rate of 0.8% (0.5-1%), despite multiple methodological difficulties biased in favour of a benign natural history. Available registries do not have the power or the design capable of providing normative guidelines for clinical decisions. The appropriate method to solve the clinical dilemma is a multicentric trial comparing the incidence of a hard clinical outcome events in approximately 2000 patients randomly allocated to a treatment group and a deferred treatment group, all followed for ten years or more. Observational studies have failed to provide reliable evidence in favour or against the preventive treatment of unruptured aneurysms. A randomized trial is in order to clarify what is the role of prevention in this common clinical problem.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".