Thirty-year Trend in Inflammatory Bowel Disease on Jeju Island, South Korea
Bibliographic record
Abstract
Background/Aims: Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is increasing in South Korea. On the other hand, there are no reports of the incidence and prevalence of IBD specific to Jeju Island, prompting the necessity of this study. Methods: In this retrospective design, the medical records of 453 patients diagnosed with IBD at Jeju National University Hospital from January 1990 to December 2019 were analyzed. Results: in 2019. The male:female ratio was 2.24:1 for CD and 1.29:1 for UC. In the CD subjects, the disease activity included remission (33.3%), mild (25.5%), moderate (30.9%), and severe (6.1%). In UC subjects, the disease activity included remission (24.0%), mild (35.4%), moderate (28.8%), and severe (6.2%). According to the Montreal classification, the cases were as follows: CD: terminal ileum (22.4%), colon (9.7%), ileocolon (66.1%), and upper gastrointestinal involvement (27.3%), and perianal fistula/abscess was present in 43.6% of subjects before or at diagnosis: UC: proctitis (43.4%), left-sided colitis (29.1%), and pancolitis (23.3%) at diagnosis. Conclusions: The incidence of IBD on Jeju Island has increased steadily for approximately 30 years but has exhibited a decline since 2017. Therefore, the incidence of IBD in Jeju is believed to have plateaued. Further study will be needed for clarification.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".