P.091 Small unruptured intracranial aneurysms: the natural history in Saskatchewan
Bibliographic record
Abstract
Background: The natural history of small unruptured intracranial aneurysms (UIAs) <7mm is 0 to 1.3% per year. Our centre provides cerebrovascular care for the entire province allowing for long-term follow-up. We studied the safety of observation for aneurysms <7mm. Methods: We performed a retrospective chart review of patients with intracranial aneurysm referred to our centre between July 2008 and April 2015. Aneurysm characteristics and current status (followed, treated, not followed), were collected along with patient factors. Follow-up duration for each aneurysm was used to calculate total follow-up in aneurysm-years. Statistical evaluation consisted of multivariate analysis and logistic regression analysis. Results: 428 patients harbouring 497 aneurysms <7mm were identified. 67 presented with rupture. Of the remaining 430 aneurysms, there was a 9.3% treatment rate. 2 cases of rupture occurred in those patients who were followed, creating a 0.5% rupture rate. 325 aneurysms were followed for 631.3 total cumulative aneurysm-years, an average of 1.9 aneurysm-years. Smoking status and hypertension associated with presence of aneurysm (p≈0.009,0.026, respectively). Conclusions: In our selected patient group there is a low yearly rate of aneurysm rupture, and observation of aneurysms <7mm is safe. Hypertension and smoking were associated with the development of aneurysm. 9.3% of patients were treated, likely leading to a reduced natural history risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".