236. CLINICAL USE OF CHEST RADIOGRAPH IN SCREENING FOR AORTIC STRUCTURAL DAMAGE IN PATIENTS WITH GIANT CELL ARTERITIS: BASELINE DATA
Bibliographic record
Abstract
Background: Giant cell arteritis (GCA) has a strong a predilection for the aorta, where inflammation is usually asymptomatic until life-threatening vascular damage occurs. Periodic screening for aortic structural damage (ASD) has been proposed, but the optimal frequency and imaging modality is unknown. This study aimed to determine the utility of chest radiograph (CXR) in identifying ASD in GCA patients at baseline. Methods: We retrospectively reviewed the electronic medical records of patients diagnosed with GCA by rheumatologists between April 2012 and December 2017. For study inclusion, patients must have met ACR 1990 classification criteria for GCA. A standardized form was used to record patient demographics, clinical variables, imaging results and outcomes. Indications for and results of CXR and advanced imaging studies (CT angiogram, MR angiogram, PET/CT) performed at baseline were recorded. Results: Of 133 patients identified on initial search, 52 patients were excluded (38 due to alternative diagnosis, 14 failed to meet ACR classification criteria), leaving 81 patients for study inclusion. Patients were predominantly female (64%), with a mean age of 71 years (+/- 8.4). See Table 1 for patient baseline characteristics. Baseline CXR results were available in 63 (78%) patients. Indications for CXR included ASD screening (12 patients, 19%), presence of symptoms (25 patients, 40%), or other/unknown reasons (26 patients, 41%). Of 63 baseline CXR available, 14 (22%) reported aortic abnormalities, including unfolding/tortuosity of the aorta (8 patients, 13%), widened mediastinum (3 patients, 5%), ectasia (2 patients, 3%), and thoracic aortic aneurysm (1 patient, 1.6%). In the single patient with thoracic aneurysm, urgent CT angiogram revealed type A dissection, and the patient underwent successful surgical repair. Conclusion: Aortic structural disease may already be present at GCA diagnosis. CXR is an easily-accessible, low-cost method that identifies possible aortic changes in 22% of patients at baseline, potentially serving to identify those that need early advanced imaging. Further studies regarding optimal screening protocols, including cost-efficacy assessments, are needed. Disclosures: None New Headache Scalp Tenderness Jaw Claudication Vision Loss Diplopia Fever Weight Loss PMR Chest pain Limb claudication Mesenteric ischemia Stroke
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".