Determining the critical size of intracranial aneurysm predisposing to subarachnoid hemorrhage in the Saudi population
Bibliographic record
Abstract
INTRODUCTION: Aneurysmal subarachnoid hemorrhage (SAH) is a devastating event with a high rate of morbidity and mortality. With the improvement of diagnostic modalities and the adoption of different screening strategies, more aneurysms are being diagnosed prior to rupture. Based on large multi-center trials, size has become the most important determinant of treatment decisions. Unfortunately, these studies did not take into account the regional and racial variations, challenging the generalizability of their results. MATERIAL AND METHODS: We conducted a retrospective analysis on a series of 192 patients harboring 213 aneurysms. RESULTS: The critical finding in our study is that the majority of patients presenting with SAH due to ruptured aneurysms are <10 mm in size. CONCLUSION: Decision to treatment of a given unruptured intracranial aneurysm should be individually assessed and not taken from general international literature as this may mistakenly apply factors from one population to another.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".