Diagnostic performance of a newly launched Canadian fast-track ultrasound clinic by rheumatologists for the diagnosis of giant cell arteritis
Bibliographic record
Abstract
BACKGROUND: Giant cell arteritis (GCA) can present diagnostic challenges and early diagnosis is crucial due to potential ischemic complications. Recent guidelines suggest that a suspected diagnosis should be confirmed with temporal artery biopsy or imaging, including ultrasound (US). In our Canadian setting, point-of-care temporal artery US was near unavailable, and biopsy remains the standard of care. We hypothesize that launching a fast-track US clinic by rheumatologists may spare the need for a temporal artery biopsy. Therefore, this study aimed to assess the diagnostic performance of US in this newly launched fast-track clinic. METHODS: In this single-center retrospective cross-sectional analysis, 99 visits were identified from the fast-track clinic between January 2020 and July 2022. Each subject had an US according to a standard protocol for suspicion of either new-onset or relapse of GCA. Ultrasonographers were rheumatologists who acquired training on vascular US techniques before launching the clinic. For each patient presenting with suspected new-onset GCA, the pretest probability was calculated using the Southend GCA probability score. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using the rheumatologist clinical diagnosis as the gold standard for GCA diagnosis. RESULTS: A total of 22 subjects had a diagnostic of GCA and 77 had another diagnostic. Patients with and without GCA were, respectively, 81.8% versus 72.7% females, had a mean age of 76.6 ± 7.7 versus. 74.8 ± 9.8 years, and a mean CRP of 73.4 ± 57.8 versus 38.3 ± 59.9 mg/l. Temporal artery US demonstrated a sensitivity of 86.3% [95% confidence interval (CI), 65.1-97.1%], a specificity of 90.9% (95% CI, 82.2-6.3%), a PPV of 73.1% (95% CI, 56.8-84.9%), and a NPV of 95.9% (95% CI, 89.0-.5%). 14 patients had a suspicion of relapse and were all correctly identified by the US. Among those with suspicion of new-onset 27, 34 and 24 US were performed for high, intermediate, and low pretest probability of GCA, respectively. The high-risk subgroup demonstrated higher PPV while similar sensitivity/specificity was observed between all three subgroups. CONCLUSION: Our results highlight the benefits of US as a key diagnostic tool for GCA, particularly when combined with clinical evaluations. An excellent discriminative ability for diagnosis of GCA was shown in this newly launched clinic suggesting that the role of TAB may need to be redefined. These findings will guide on broader implementation of US programs for GCA.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".