Investigating the Association between Aortic Arch Variants and Intracranial Aneurysms
Bibliographic record
Abstract
BACKGROUND: There is an association between anterior cerebral artery vessel asymmetry and anterior communicating artery aneurysm, presumably based on flow dynamics. The purpose of this study is to investigate the potential relationship between aortic arch branching patterns and incidence of intracranial aneurysm. METHODS: This study included patients scanned over 1 year at our tertiary care center who underwent high-resolution imaging (computed tomography angiography or digital subtracted angiogram) of the head and neck arteries, aortic arch, and superior mediastinum. Exclusion criteria included patients with suboptimal images. Patient age, gender, aortic arch branching pattern, and the presence, location, and number of aneurysms were documented. RESULTS: Among the 1082 patients analyzed, 250 (23%) patients had a variant aortic arch branching pattern, 22 (8.8%) of whom had aneurysms. There were 104 patients with 126 aneurysms, with majority of patients with normal aortic arch branching pattern (n = 82, 79%). The most common variant was a common origin of the left common carotid artery and brachiocephalic trunk with or without direct origin of the left vertebral artery. Twenty-two patients with aneurysms had an aberrant aortic arch (21%), compared to 232 patients without an aneurysm (24%). Fischer exact test showed no statistically significant difference between the incidence of aneurysm with different aortic arch variant groups (two-tailed p-value = 0.715). CONCLUSION: To our knowledge, this is the first study to examine the association between aortic arch branching patterns and incidence of intracranial aneurysm. No significant association was found between aortic arch branching pattern and the incidence of intracranial aneurysm.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".