Diagnosis of Inflammatory Bowel Disease–Associated Peripheral Arthritis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD)-associated peripheral spondyloarthritis (pSpA) decreases quality of life and remains poorly understood. Given the prevalence of this condition and its negative impact, it is surprising that evidence-based disease definitions and diagnostic strategies are lacking. This systematic review summarizes available data to facilitate development and validation of diagnostics, patient-reported outcomes, and imaging indices specific to this condition. METHODS: A literature search was conducted. Consensus or classification criteria, case series, cross-sectional studies, cohort studies, and randomized controlled trials related to diagnosis were included. RESULTS: A total of 44 studies reporting data on approximately 1500 patients with pSpA were eligible for analysis. Data quality across studies was only graded as fair to good. Due to large heterogeneity, meta-analysis was not possible. The majority of studies incorporated patient-reported outcomes and a physical examination. A total of 13 studies proposed or validated screening tools, consensus, classification, or consensus criteria. A total of 28 studies assessed the role of laboratory tests, none of which were considered sufficiently accurate for use in diagnosis. A total of 17 studies assessed the role of imaging, with the available literature insufficient to fully endorse any imaging modality as a robust diagnostic tool. CONCLUSIONS: This review highlights existing inconsistency and lack of a clear diagnostic approach for IBD-associated pSpA. Given the absence of an evidence-based approach, a combination of existing criteria and physician assessment should be utilized. To address this issue comprehensively, our future efforts will be directed toward pursuit of a multidisciplinary approach aimed at standardizing evaluation and diagnosis of IBD-associated pSpA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".