Ruptured intracranial infectious aneurysms: Single Canadian center experience
Bibliographic record
Abstract
Background: Ruptured intracranial infected aneurysms (IIAs) are relatively rare, but they portend high mortality. To the best of our knowledge, there is no Canadian case series on IIA, as well there is a relative paucity of international published experiences. Our purpose is to share the experience of a single Canadian tertiary center in managing ruptured IIA and to conduct a systematic review. Methods: We did a retrospective case review series of adult patients with ruptured IIA treated at our institution. Second, we conducted a systematic review of the literature on ruptured IIA between 2011 and 2021 inclusive. Results: At our institution, of a total eight cases with ruptured IIA, four were treated endovascularly and two by surgical bypass. For the systematic review, we included nine noncomparative studies with a total of 509 patients (318 males) and at least 437 ruptured IIA aneurysms. Favorable outcome was specified for 63.3% of patients (n = 57). Regarding ruptured IIA, favorable clinical outcome was described in 59.3% (n = 16). Conclusion: This study highlights a single Canadian tertiary center experience in the management of IIA and compares it to the global trends of the past 10 years in a systematic review.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".