Disease course of inflammatory bowel disease unclassified in a European population‐based inception cohort: An Epi‐IBD study
Bibliographic record
Abstract
BACKGROUND AND AIM: A definitive diagnosis of Crohn's disease (CD) or ulcerative colitis (UC) is not always possible, and a proportion of patients will be diagnosed as inflammatory bowel disease unclassified (IBDU). The aim of the study was to investigate the prognosis of patients initially diagnosed with IBDU and the disease course during the following 5 years. METHODS: The Epi-IBD study is a prospective population-based cohort of 1289 IBD patients diagnosed in centers across Europe. Clinical data were captured prospectively throughout the follow-up period. RESULTS: Overall, 476 (37%) patients were initially diagnosed with CD, 701 (54%) with UC, and 112 (9%) with IBDU. During follow-up, 28 (25%) IBDU patients were changed diagnoses to either UC (n = 20, 71%) or CD (n = 8, 29%) after a median of 6 months (interquartile range: 4-12), while 84 (7% of the total cohort) remained IBDU. A total of 17 (15%) IBDU patients were hospitalized for their IBD during follow-up, while 8 (7%) patients underwent surgery. Most surgeries (n = 6, 75%) were performed on patients whose diagnosis was later changed to UC; three of these colectomies led to a definitive diagnosis of UC. Most patients (n = 107, 96%) received 5-aminosalicylic acid, while 11 (10%) patients received biologicals, of whom five remained classified as IBDU. CONCLUSIONS: In a population-based inception cohort, 7% of IBD patients were not given a definitive diagnosis of IBD after 5 years of follow-up. One in four patients with IBDU eventually was classified as CD or UC. Overall, the disease course and medication burden in IBDU patients were mild.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".