A Joint Effort: Improving the Identification of Spondyloarthritis in Patients With Inflammatory Bowel Disease
Bibliographic record
Abstract
In individuals with inflammatory bowel disease (IBD), extraintestinal manifestations (EIMs) represent a significant burden of illness, with reported prevalence rates of up to 50%.1 Of the various types of EIMs, the most commonly involved organ system is the musculoskeletal system. The 2 major clinical phenotypes are axial spondyloarthritis (axSpA) and peripheral SpA, which have been reported in up to 20% and 50% of patients with IBD, respectively.2,3 Despite the high prevalence of rheumatologic EIMs in IBD, no systematic method for screening of inflammatory arthritis is available for use in clinical practice. To date, only one of the major gastrointestinal societies (the European Crohn’s and Colitis Organization) has published clinical guidelines on the management of EIMs, and the current United States–based guidelines on treatment of moderate to severe IBD do not include recommendations on the diagnosis or treatment of EIMs.4-6 Given the lack of standardized screening methods, various attempts have been made to improve the assessment of SpA in IBD populations. Two screening tools, … Address correspondence to Dr. S.J. Hong, 305 East 33rd Street, New York, NY 10016, USA. Email: simon.hong{at}nyulangone.org.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".