Inflammatory Bowel Diseases and Coexisting Spondyloarthritis: A Neglected and too Often Under-Reported Association by Radiologists. A Multicenter Study by Italian Research Group of Imaging in Rheumatology
Bibliographic record
Abstract
Purpose: The purpose of this study was to evaluate the prevalence and the underreporting rate of sacroiliitis (SI) in a large cohort of patients with biopsy-proved Crohn’s disease (CD) who underwent magnetic resonance enterography (MRE) or computed tomography enterography (CTE). Materials and Methods: Patients with CD were recruited from eight Italian health centers in the period from January 2013 to December 2017. Disease activity was recorded according to the CD activity index (CDAI). The scans were read by two blinded readers who defined the presence of SI according to Assessment of SpondyloArthritis International Society (ASAS) classifications and European League Against Rheumatism (EULAR) recommendations. Moreover, SI was scored using a simplified Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system. Results: Interobserver agreement in diagnosing SI on imaging was good (K = 0.72–0.83). SI was diagnosed in 129 (14.4%, 54 men, 75 women) out of 894 patients; however, sacroiliac joint (SIJ) abnormalities were not mentioned in the radiological reports of 112 patients (86%). Fifty (38.7%) out of 129 patients also underwent a subsequent SIJ evaluation through a dedicated MRI protocol to confirm SI. SI was found in a higher percentage of patients with “active” than “inactive” CD (18% vs. 4%). Conclusion: This study confirms the feasibility of CTE and MRE for the screening of SI in CD patients; however, it also underlines the remarkable problem concerning the underreporting of this entity in radiological practice.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".