Challenges of Assessment of SpondyloArthritis international Society Criteria in Real-World Colombian Patients With Spondyloarthritis: A Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE: The Assessment of SpondyloArthritis international Society (ASAS) criteria classify spondyloarthritis (SpA) based on clinical presentation. Although widely applied, the measure's performance in Colombia's population remains unclear. This study aimed to characterize a Colombian SpA cohort, identify factors associated with peripheral SpA (pSpA), compare SpA subtypes, assess the performance of ASAS criteria, and compare the ASAS with modified New York (mNY) and European Spondyloarthropathy Study Group (ESSG) criteria. METHODS: This cross-sectional study included patients with newly diagnosed SpA by ≥ 1 expert rheumatologist. Participants completed a structured survey, physical examination, imaging, and laboratory tests. Researchers classified patients using ASAS, ESSG, and mNY criteria and compared clinical characteristics across groups. Finally, the performance of the ASAS criteria relative to the rheumatologist's diagnosis, mNY, and ESSG was analyzed. RESULTS: The study analyzed 461 patients with SpA, of whom 58.1% had pSpA. Patients with axial SpA (axSpA) and pSpA differed significantly in age at onset, initial symptoms, buttock pain, Schober test, sacroiliitis, and HLA alleles. The ASAS criteria demonstrated a sensitivity of 90.8% when compared to rheumatologist diagnosis. Notably, 33.6% and 36.6% of patients classified as having radiographic axSpA (r-axSpA) by mNY or ESSG, respectively, were misclassified as pSpA under ASAS due to unmet entry criteria for axSpA. CONCLUSION: This large Colombian SpA cohort, predominantly comprising patients with pSpA, revealed distinct clinical and imaging features between axSpA and pSpA. The ASAS criteria showed high sensitivity but failed to classify a subset of patients with radiographic sacroiliitis as having r-axSpA, highlighting limitations in its entry criteria for axSpA.
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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 | 0.005 | 0.013 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".