Multicenter Validation of the DETAIL Questionnaire for the Screening of Spondyloarthritis in Patients With Inflammatory Bowel Diseases
Bibliographic record
Abstract
OBJECTIVE: Spondyloarthritis (SpA) is among the most frequent extraintestinal manifestations of inflammatory bowel diseases (IBD). In this study, we aimed to validate the DETection of Arthritis in Inflammatory boweL diseases (DETAIL) questionnaire in a multicenter cohort of patients with IBD enrolled at 11 gastroenterology units. METHODS: From October 2018 to March 2019, consecutive adult patients with IBD, either Crohn disease or ulcerative colitis, independently filled out the DETAIL questionnaire in the outpatient waiting room. Within 2 weeks a blinded rheumatologist assessed all the patients, irrespective of the DETAIL results, and classified them to be affected or not by SpA. The performance of the questions was evaluated through Bayesian analysis. RESULTS: Overall, 418 patients with IBD filled out the DETAIL questionnaire. Upon rheumatological evaluation, 102 (24.4%) patients received a diagnosis of SpA. Of the 6 questions, the best performances were found in question 6 [positive likelihood ratio (LR)+ 3.77], reporting inflammatory back pain at night, and in question 3 (LR+ 3.31), exploring Achilles enthesitis. The presence of back pain lasting > 3 months (LR+ 2.91), back pain with inflammatory features (LR+ 2.55), and a history of dactylitis (LR+ 2.55), also showed a fairly good performance, whereas a history of peripheral synovitis was slightly worse (LR+ 2.16). The combination of at least 3 questions answered affirmatively yielded a posttest probability of SpA of 80% or more. The presence of alternative diagnoses, such as osteoarthritis or fibromyalgia, represented a minor confounder. CONCLUSION: The DETAIL questionnaire is a useful tool for the early detection of SpA in IBD.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".