Risk Factors for Permanent Visual Loss in Biopsy-proven Giant Cell Arteritis: A Study of 339 Patients
Bibliographic record
Abstract
OBJECTIVE: To determine the risk factors for permanent visual loss (PVL) in patients with biopsy-proven giant cell arteritis (GCA) and the usefulness of the factors in clinical practice. METHODS: From 1976 through 2015, the clinical charts and laboratory results of 339 patients with biopsy-proven GCA were recorded prospectively at the time of diagnosis. We used multivariable logistic regression analysis to determine which of 24 pretreatment characteristics were associated with PVL. RESULTS: Visual ischemic manifestations occurred in 108 patients, including PVL in 53 (16%), bilaterally in 15 patients (28%). The independent predictors associated with an increased risk of PVL were age (OR 1.06, 95% CI 1.01-1.12, p = 0.01), a history of transient visual ischemic symptoms (OR 2.62, 95% CI 1.29-5.29, p < 0.01), and jaw claudication (OR 2.11, 95% CI 1.09-4.10, p = 0.03). The presence of fever (OR 0.30, 95% CI 0.14-0.64, p < 0.01) and rheumatic symptoms (OR 0.23, 95% CI 0.10-0.57, p = 0.001) were associated with a markedly reduced risk of developing visual loss (3.7% if features were both present). No laboratory variables were independently associated with PVL. CONCLUSION: The visual ischemic risk of untreated GCA can be readily estimated upon simple clinical findings, but not laboratory variables. However, we did not identify a subgroup of patients carrying no risk of developing visual loss. Glucocorticoid treatment remains, therefore, urgent for any patient with a high clinical suspicion index.
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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".