Angles of the Branches of the Visceral Aorta: Implications for Complex Aneurysm Repairs
Bibliographic record
Abstract
Thoracoabdominal aortic aneurysms can require custom designed branched stent‐grafts. Visceral and renal artery orientations can change as more of this segment becomes aneurysmal. This study's purpose was to determine these orientations in infrarenal aneurysms as a baseline to compare to more complex proximal aneurysms. Aquarius TeraRecon 3D imaging software was used for morphological assessment of CT scans for 20 Infrarenal aneurysms. (15M, 5F, mean age=73.7). Four take off angles were measured. The clock‐face position (CFP) was noted in transverse sections for each. The direction of take off of the renal arteries was assessed (anterior, orthogonal and posterior) and maximal aortic aneurysm diameter was taken. The average take off angle was 63.06° in the Left Renal (LRA), 55.57° in the Right Renal (RRA), 60.07° in the Superior Mesenteric (SMA) and 56.82° in the Celiac Trunk (CT). The mode for CFP was 3:00 (n=8) in LRA, 10:00 (n=10) in RRA, 1:00 (n=9) in SMA and 1:00 (n=8) in CT. The mode for direction of take off angle was orthogonal (n=10) for LRA and anterior (n=12) for RRA. The mean maximal aneurysmal diameter was 57.95mm. The data suggests little variability in patients with Infrarenal aneurysms. This information will be used as a baseline as more proximal aneurysms are assessed. Grant Funding Source : Departmental
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".