Giant Cell Arteritis with or without Aortitis at Diagnosis. A Retrospective Study of 22 Patients with Longterm Followup
Bibliographic record
Abstract
OBJECTIVE: Studies have shown that aortitis may be present in half the patients with recent-onset giant cell arteritis (GCA). We assessed whether aortitis at diagnosis affects longterm outcome in patients with GCA. METHODS: We retrospectively analyzed the longterm outcome of a prospective cohort of 22 patients with biopsy-proven GCA who all had aortic computed tomography (CT) evaluation at the time of diagnosis of GCA between May 1998 and November 1999. Longterm outcome, especially vascular events such as aortic aneurysm, mortality, relapses of GCA, and requirement for steroids, was assessed in 2011 by chart review and patient/physician interviews. RESULTS: At disease onset, 10/22 patients had aortitis on CT scan. Patients with and without aortitis had similar baseline characteristics, including cardiovascular risk profile. At the time of the study, 12/22 (57%) patients had died. Vascular causes of death were more frequent in patients with aortitis (5/7 vs 0/5; p = 0.02). A higher number of vascular events was noted in patients with aortitis (mean events per patient 1.33 vs 0.25; p = 0.009). Stroke was more frequent in patients with aortitis. These patients seemed to exhibit a more chronic or relapsing disease course, and they were less likely to completely discontinue steroid therapy (p = 0.009, log-rank test). CONCLUSION: Our study suggests for the first time that inflammatory aortic involvement present at onset of GCA could predict a more chronic/relapsing course of GCA, with higher steroid requirements and an increased risk for vascular events in the long term.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".