High Prevalence of Previously Undiagnosed Axial Spondyloarthritis in Patients Referred With Anterior Uveitis and Chronic Back Pain: The SpEYE Study
Bibliographic record
Abstract
OBJECTIVE: To reduce the diagnostic delay in axial spondyloarthritis (axSpA), guidelines recommend referring patients with acute anterior uveitis (AAU) and chronic back pain (CBP) to a rheumatologist. This observational study in daily practice evaluated the prevalence of previously unrecognized axSpA in patients with AAU who were referred by ophthalmologists because of concurrent CBP. METHODS: All patients with AAU referred with CBP (≥ 3 months, age of onset < 45 yrs) from 5 ophthalmology clinics underwent rheumatologic assessment, including pelvic radiographs. Patients with previously diagnosed rheumatic disease and AAU due to other causes were excluded. The primary endpoint was a clinical axSpA diagnosis by the rheumatologist. RESULTS: Eighty-one patients fulfilled the referral criteria (52% male, 56% HLA-B27 positive, median age 41 yrs, median CBP duration 10 yrs). In total, 58% (n = 47) had recurring AAU, of whom 87% already had CBP during previous AAU attacks. After assessment, 23% (n = 19) of patients were clinically diagnosed with definite axSpA (10/19 radiographic), 40% (n = 32) with suspicion of axSpA, and 37% (n = 30) with no axSpA. AxSpA was diagnosed more often in men (33% of the men vs 13% of the women). CONCLUSION: A high prevalence of axSpA was found in patients with AAU referred because of CBP. There was substantial diagnostic delay in the majority of patients with recurring AAU, as many already had CBP during previous AAU flares. In AAU, screening for CBP and prompt referral has a high diagnostic yield and should consistently be promoted among ophthalmologists.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".