Positron Emission Tomography/Computerized Tomography in Newly Diagnosed Patients with Giant Cell Arteritis Who Are Taking Glucocorticoids
Bibliographic record
Abstract
OBJECTIVE: Large vessel uptake on positron emission tomography/computerized tomography (PET/CT) supports the diagnosis of giant cell arteritis (GCA). Its value, however, in patients without arteritis on temporal artery biopsy and in those receiving glucocorticoids remains unknown. We compared PET/CT results in GCA patients with positive (TAB+) and negative temporal artery biopsies (TAB-), and controls. METHODS: Patients with new clinically diagnosed GCA starting treatment with glucocorticoids underwent temporal artery biopsy and PET/CT. Using a visual semiquantitative approach, 18F-fluorodeoxyglucose (FDG) uptake was scored in 8 vascular territories and summed overall to give a total score in patients and matched controls. RESULTS: Twenty-eight patients with GCA and 28 controls were enrolled. Eighteen patients with GCA were TAB+. Mean PET/CT scores after an average of 11.9 days of prednisone were higher in patients with GCA compared to controls, for both total uptake (10.34 ± 2.72 vs 7.73 ± 2.56; p = 0.001), and in 6 of 8 specific vascular territories. PET/CT scores were similar between TAB+ and TAB- patients with GCA. The optimal cutoff for distinguishing GCA cases from controls was a total PET/CT score of ≥ 9, with an area under the receiver-operating characteristic curve of 0.75, sensitivity 71.4%, and specificity 64.3%. Among patients with GCA, these measures correlated with greater total PET/CT scores: systemic symptoms (p = 0.015), lower hemoglobin (p = 0.009), and higher platelet count (p = 0.008). CONCLUSION: Vascular FDG uptake scores were increased in most patients with GCA despite exposure to prednisone; however, the sensitivity and specificity of PET/CT in this setting were lower than those previously reported.
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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) | 0.001 | 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 | 0.001 |
| 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".