Spectrum and Outcome of Noninfectious Aortitis
Bibliographic record
Abstract
Objective To assess the spectrum and long-term outcome of patients with noninfectious aortitis. Methods We performed a retrospective multicenter study of 353 patients (median age at diagnosis was 62 [IQR 46–71] yrs and 242 [68.6%] patients were women) with noninfectious aortitis. Factors associated with vascular complications were assessed in multivariate analysis. Results We included 136 patients with giant cell arteritis (GCA), 96 with Takayasu arteritis (TA), 73 with clinically isolated aortitis (CIA), and 48 with aortitis secondary to inflammatory diseases (including Behçet disease, relapsing polychondritis, IgG4-related disease, Cogan syndrome, ankylosing spondylitis). After a median follow-up of 52 months, vascular complications were observed in 32.3%, revascularizations in 30% of patients, and death in 7.6%. The 5-year cumulative incidence of vascular complications was 58% (95% CI 41–71), 20% (95% CI 13–29), and 19% (95% CI 11–28) in CIA, GCA, and TA, respectively. In multivariate analysis, male sex (HR 2.10, 95% CI 1.45–3.05, P < 0.0001) and CIA (HR 1.76, 95% CI 1.11–2.81, P = 0.02) were independently associated with vascular complications. Conclusion Noninfectious aortitis accounts for significant morbidity and mortality. CIA seems to carry the highest rate of vascular complications.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".