The A1-A2 Diameter Ratio May Influence Formation and Rupture Potential of Anterior Communicating Artery Aneurysms
Bibliographic record
Abstract
BACKGROUND: Specific morphological factors contribute to the hemodynamics of the anterior communicating artery (AComA). No study has examined the role of the A2 segment on AComA aneurysm presence and rupture. OBJECTIVE: To examine the possibility that the ratio between A1 and A2 segments (A1-2 ratio) represents an independent risk factor for presence and rupture of AComA aneurysms (AComAAs). METHODS: A retrospective review of an institutional aneurysm database was performed; patients with ruptured and unruptured AComAAs were identified. Two control groups were selected: group A (posterior circulation aneurysms) and group B (patients without intracranial aneurysms or other vascular malformations). Measurements of A1 and A2 diameters were obtained from digital subtraction angiography (64.1% of 3-D rotational digital subtraction angiography), and the A1-2 ratio calculated. RESULTS: From January 2009 to April 2011, 156 patients were identified (52 AComAAs, 54 control group A, and 50 control group B). Mean age at the time of presentation was 56.09 years. Compared with both control groups, patients with AComAAs had greater A1 diameter (P < .01) and A1-2 ratio (P < .001) and smaller A2 diameter (P < .01). The A1-2 ratio correlated positively with the presence of AComAAs (P < .001). Ruptured AComAAs were smaller than unruptured ones (5.91 mm vs 9.25 mm, P = .02) and associated with a higher A1-2 Ratio (P = .02). The presence of a dominant A1 did not predict AComAA rupture (P = .15). The A1-2 ratio correlated positively with the presence of ruptured AComAAs (P = .04). CONCLUSION: A1-2 ratio correlates positively with the presence and rupture of AComAAs and may facilitate treatment decision in cases of small, unruptured AComAAs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".