Assessment of Giant Cell Arteritis–Associated Visual Outcomes at a Tertiary Hospital in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: There are limited data concerning outcomes in those with giant cell arteritis (GCA)-associated vision changes (GCAVCs). We estimated the association of intravenous (IV), compared to oral, glucocorticoids (GCs) with outcomes in GCAVCs. METHODS: We conducted a retrospective cohort study at a tertiary healthcare facility in Ontario, Canada. Individuals aged ≥ 50 years with an International Classification of Diseases, 10th revision, diagnostic code for GCA associated with a healthcare visit between November 2017 to December 2023 were identified for inclusion. Diagnoses of GCA were verified as the final diagnosis of the treating clinician and were required to be supported by histologic, radiographic, and/or biochemical evidence of inflammatory vasculopathy. GCAVCs were identified by clinical assessments. Treatment exposures were defined as whether the individual was first exposed to IV or oral GCs. The primary outcome was reported visual improvement after treatment. We used logistic regression to estimate treatment effects, adjusting for demographic and disease factors. RESULTS: In 289 patients with GCA, 77 (26.6%) had GCAVCs. Of these, 70.1% of GCAVCs led to permanent vision loss, and visual recovery was seen in 16% of participants. We found no difference in outcomes for those first treated with IV vs oral GCs (adjusted odds ratios 0.43-1.72; 95% CI 0.02-123.68). CONCLUSION: GCAVCs are common and frequently associated with permanent vision loss. Although the precision of our results was limited by sample size, we did not find evidence that receiving IV GCs before oral GCs was associated with visual improvement in GCAVCs.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".