Familial Intracranial Aneurysms
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Previous studies have suggested that family members with intracranial aneurysms (IAs) often harbor IAs in similar anatomic locations. IA location is important because of its association with rupture. We tested the hypothesis that anatomic susceptibility to IA location exists using a family-based IA study. METHODS: We identified all affected probands and first-degree relatives (FDRs) with a definite or probable phenotype in each family. We stratified each IA of the probands by major arterial territory and calculated each family's proband-FDR territory concordance and overall contribution to the concordance analysis. We then matched each family unit to an unrelated family unit selected randomly with replacement and performed 1001 simulations. The median concordance proportions, odds ratios (ORs), and P values from the 1001 logistic regression analyses were used to represent the final results of the analysis. RESULTS: There were 323 family units available for analysis, including 323 probands and 448 FDRs, with a total of 1176 IAs. IA territorial concordance was higher in the internal carotid artery (55.4% versus 45.6%; OR, 1.54 [1.04-2.27]; P=0.032), middle cerebral artery (45.8% versus 30.5%; OR, 1.99 [1.22-3.22]; P=0.006), and vertebrobasilar system (26.6% versus 11.3%; OR, 2.90 [1.05-8.24], P=0.04) distributions in the true family compared with the comparison family. Concordance was also higher when any location was considered (53.0% versus 40.7%; OR, 1.82 [1.34-2.46]; P<0.001). CONCLUSIONS: In a highly enriched sample with familial predisposition to IA development, we found that IA territorial concordance was higher when probands were compared with their own affected FDRs than with comparison FDRs, which suggests that anatomic vulnerability to IA formation exists. Future studies of IA genetics should consider stratifying cases by IA location.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.008 | 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".