Takayasu Arteritis and Spondyloarthritis: Coincidence or Association? A Study of 14 Cases
Bibliographic record
Abstract
OBJECTIVE: Spondyloarthritis (SpA) and Takayasu arteritis (TA) are 2 chronic inflammatory diseases; their coexistence in a single patient is uncommon. The aims of our study were to describe clinical features of patients having SpA associated with TA and to identify some characteristics of the types of patients with SpA associated with TA. We also analyzed treatments used in this context. METHODS: This French multicenter retrospective survey called for observations on behalf of the Club Rhumatismes et Inflammations, with a standardized questionnaire established by the investigators. RESULTS: We included 14 patients (women: 10/14; median age at SpA diagnosis: 43.5 yrs, ranging from 19 to 63). Subtypes of SpA were ankylosing spondylitis (n = 11), psoriatic arthritis (n = 2), and synovitis, acne, pustulosis, hyperostosis, and osteitis syndrome (n = 1). HLA-B27 was positive in 3 cases, negative in 9, and unknown in 2. SpA was diagnosed before TA in 13 cases. Imaging findings compatible with the diagnosis of TA were found with computed tomography (11/14) and/or Doppler ultrasound (10/14). Laboratory tests showed increased acute-phase reactants in all cases (C-reactive protein ≥ 25 mg/l in 71% of the cases). All patients except 1 received corticosteroids and 7 were treated with anti-tumor necrosis factor (anti-TNF). CONCLUSION: Association of SpA and TA is rare but probably not coincidental. Peripheral pulse palpation and vascular auscultation should be systematic and are the first indicators of TA in patients with SpA. Moreover, increased acute-phase reactants during SpA followup should lead to search for TA. Finally, there are therapeutic implications because anti-TNF are efficient in SpA and might be efficient in TA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".