Factors Associated with Relapse and Dependence on Glucocorticoids in Giant Cell Arteritis
Bibliographic record
Abstract
OBJECTIVE: To identify characteristics and factors associated with relapse and glucocorticoid (GC) dependence in patients with giant cell arteritis (GCA). METHODS: We retrospectively analyzed 326 consecutive patients with GCA followed for at least 12 months. Factors associated with relapse and GC dependence were identified in multivariable analyses. RESULTS: The 326 patients (73% women) were followed up for 62 (12-262) months. During followup, 171 (52%) patients relapsed, including 113 (35%) who developed GC dependence. Relapsing patients had less history of stroke (p = 0.01) and presented large-vessel vasculitis (LVV) more frequently on imaging (p = 0.01) than patients without relapse. During the first months, therapeutic strategy did not differ among relapsing and nonrelapsing patients. GC-dependent patients were less likely to have a history of stroke (p = 0.004) and presented LVV on imaging more frequently (p = 0.005) than patients without GC-dependent disease. In multivariable analyses, LVV was an independent predictive factor of relapse (HR 1.49, 95% CI 1.002-2.12; p = 0.04) and GC dependence (OR 2.19, 95% CI 1.19-4.05; p = 0.01). Conversely, stroke was a protective factor against relapse (HR 0.21, 95% CI 0.03-0.68; p = 0.005) and GC-dependent disease (OR 0.10, 95% CI 0.001-0.31; p = 0.0005). Patients with a GC-dependent disease who received a GC-sparing agent had a shorter GC treatment duration than those without (p = 0.008). CONCLUSION: In this study, LVV was an independent predictor of relapse and GC dependence. Further prospective studies are needed to confirm these findings and to determine whether patients with LVV require a different treatment approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".