Ascending Aortic Length and Its Association With Type A Aortic Dissection
Bibliographic record
Abstract
Background The aim of this study was to determine the role of ascending aortic length and diameter in type A aortic dissection. Methods and Results Computed tomography scans from patients with acute type A dissections (n=51), patients with proximal thoracic aortic aneurysms (n=121), and controls with normal aortas (n=200) were analyzed from aortic annulus to the innominate artery using multiplanar reconstruction. In the control group, ascending aortic length correlated with diameter ( r 2 =0.35, P <0.001), age ( r 2 =0.17, P <0.001), and sex ( P <0.001). As a result of immediate changes in aortic morphology at the time of acute dissection, predissection lengths and diameters were estimated based on models from published literature. Ascending aortic length was longer in patients immediately following acute dissection (median, 109.7 mm; interquartile range [IQR], 101.0–115.1 mm), patients in the estimated predissection group (median, 104.2 mm; IQR, 96.0–109.3 mm), and patients in the aneurysm group (median, 107.0 mm; IQR, 99.6–118.7 mm) in comparison to controls (median, 83.2 mm; IQR, 74.5–90.7 mm) ( P <0.001 all comparisons). The diameter of the ascending aorta was largest in the aneurysm group (median, 52.0 mm; IQR, 45.9–58.0 mm), followed by the dissection group (median, 50.3 mm; IQR, 46.6–57.5 mm), and not significantly different between controls and the estimated predissection group (median, 33.4 mm [IQR, 30.7–36.7 mm] versus 35.2 mm [IQR, 32.6–40.3 mm], P =0.09). After adjustment for diameter, age, and sex, the estimated predissection aortic lengths were 16 mm longer than those in the controls and 12 mm longer than in patients with nondissected thoracic aneurysms. Conclusions The length of the ascending aorta, after adjustment for age, sex, and aortic diameter, may be useful in discriminating patients with type A dissection from normal controls and patients with nondissected thoracic aneurysms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".