Surgical Pathology of Noninfectious Ascending Aortitis: A Study of 45 Cases With Emphasis on an Isolated Variant
Bibliographic record
Abstract
BACKGROUND: Aortitis is emerging as an important cause of ascending aortic aneurysm in the elderly. Its features have not been described in a surgical population. DESIGN: Retrospective clinicopathologic review of 45 cases of active noninfectious aortitis among 513 consecutive ascending aortic resections (1985 to 1999). METHODS: Clinical data were collected from medical records. Histopathologic features were recorded during review of slides stained with hematoxylin-eosin and Verhoeff-van Gieson. Cases were categorized by predefined clinical criteria. Clinicopathologic features were compared among groups, with emphasis on unsuspected aortitis without systemic arteritis. RESULTS: The 2 largest groups were isolated aortitis (47%) and giant cell arteritis (31%). Other aortitis groups included Takayasu (14%), rheumatoid (4%), and unclassified (4%). Patients with isolated aortitis and giant cell arteritis were generally women (80%; mean age 73 y). All 6 with Takayasu arteritis were women (mean age 26). Although giant cell arteritis and isolated aortitis were histologically indistinguishable, their clinical courses differed substantially. Among 21 patients with isolated aortitis (2 treated with corticosteroids), only 10% later developed aortic aneurysms. In contrast, of 14 patients with giant cell arteritis (11 treated with corticosteroids), 21% subsequently developed aneurysms (P=0.09). CONCLUSIONS: Aortitis primarily affected women. Patients with isolated aortitis and giant cell arteritis were generally older than 50 years and, by definition, those with Takayasu arteritis were younger. In patients with isolated aortitis, outcomes were generally good, despite the absence of anti-inflammatory therapy. Accordingly, a conservative approach may be warranted for managing this subset of patients with aortitis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".