O09 Ultrasound Compared with Biopsy in the Diagnosis of Suspected Giant Cell Arteritis
Bibliographic record
Abstract
Background: GCA is a relatively common form of systemic vasculitis that, if untreated, can lead to permanent sight loss. We compared the effectiveness and cost-effectiveness of ultrasound (US) with temporal artery biopsy (which can be negative in 10–30% of true cases) in the diagnosis of patients with suspected GCA. Methods: We undertook a prospective multicentre cohort study of temporal artery biopsy compared with US of the temporal and axillary arteries for diagnosis of newly suspected GCA. Sonographers received training and examined 10 healthy subjects and 1 patient with active GCA before participating in the study. We recruited patients referred to secondary care with suspected new-onset GCA. The main outcome measures were sensitivity, specificity and cost-effectiveness using a reference diagnosis derived from the final clinical diagnosis, ACR classification criteria for GCA and expert review. The cost-effectiveness analysis compared treatment costs, the impact of steroid toxicity in false-positive cases and the impact of GCA complications in false-negative cases for the two tests and different testing strategies in combination with clinical judgement.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".