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Introduction of Temporal Artery and Large Vessel Ultrasound for the Diagnosis of Giant Cell Arteritis: A Single Canadian Center Experience

2025· article· en· W4411846620 on OpenAlexaffvenueabout
Raymond Chu, Tara Swami, Mohammad Bardi

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsUniversity of British ColumbiaUniversity of Ottawa
Fundersnot available
KeywordsMedicineGiant cell arteritisTemporal arterySingle CenterArteritisCenter (category theory)RadiologyUltrasoundPathologyVasculitisSurgeryDisease

Abstract

fetched live from OpenAlex

Objectives Diagnostic imaging in giant cell arteritis (GCA) is increasingly being used to replace biopsy (TAB), with the advent of temporal artery and large vessel ultrasound (TA/LV US) showing better sensitivity and comparable specificity to TAB.[1] The purpose of our study is to share and validate our real-world experience since introducing TA/LV US at The Ottawa Hospital. Methods A retrospective chart review was performed on patients referred to RC for query GCA between October 2023-May 2024. We included only suspected new cases of GCA, excluding Takayasu’s arteritis (TAK). Patients were also excluded if they took glucocorticoids for >30 days (known to reduce the sensitivity US). Our TA/LV US protocol measured the intimal medial thickness (IMT) in transverse and longitudinal views of the common/frontal/parietal/facial/subclavian/axillary/carotid arteries. Positive scans were identified based on increased intimal media thickness and presence of halos/slope signs. We extracted patient demographics, prednisone duration, US and TAB results, and final clinical diagnosis in at least 3 months follow-up. The primary outcome measure was the sensitivity and specificity of TA/LV US and TAB taking the clinical diagnosis as the reference standard. Results A total of 170 patients underwent a TA/LV US during this timeframe. Two patients were referred for TAK and of the remaining 168, 77 were excluded given duration of prednisone use (Figure). Of the 91 patients remaining, the median age was 73 (interquartile range [IQR], 60-79) years and 54 (59%) were female. 39/91 (43%) patients were given a clinical diagnosis of GCA. Of these, 35/39 (89.7%) had a positive TA/LV US. Of the 58/91 patients who underwent TAB, 35 (60%) were positive. 11/39 patients diagnosed with GCA with US alone and no TAB. Sensitivity and specificity for TA US was 89.7% and 100% while TAB was 85.7% and 100% respectively. After ≥3 months of follow-up 6/52 (12%) of those not diagnosed with GCA were diagnosed with an alternate ailment (Still’s, lymphoma, skull invasive meningioma, staphylococcus aureus bacteremia, mast cell activation syndrome and a tooth abscess). Conclusion Our brief real-world experience with TA/LV US has demonstrated comparable specificity and marginally better sensitivity for the diagnosis of GCA, although longer term data and follow-up would be required to better understand the role for each modality moving forward. Given emerging use of TA/LV US in the diagnosis of GCA and operator dependency, we highlight the importance of validation of technique in the diagnosis of GCA. [1.] Schmidt WA. Rheumatology 2018;57(Suppl_2):ii22-31.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.008
GPT teacher head0.238
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes3
Has abstractyes

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