Suboptimal disease control and contributing factors in Italian IBD patients: The IBD-PODCAST Study
Bibliographic record
Abstract
BACKGROUND AND AIM: Suboptimal disease control (SDC) and its contributing factors in IBD according to STRIDE-II criteria is unclear. IBD-PODCAST was a non-interventional, international, multicenter real-world study to assess this. METHODS: Data from the Italian IBD cohort (N=220) are presented here. Participants aged ≥19 with confirmed IBD diagnosis of ≥1 year were consecutively enrolled. A retrospective chart review and cross-sectional assessment by physicians and patients within the past 12 months were performed. SDC or optimal disease control was assessed using adapted STRIDE-II criteria. RESULTS: At the index date, 53.4 % of 116 CD patients and 49.0 % of 104 UC patients had SDC, mainly attributed to a Short Inflammatory Bowel Disease Questionnaire score <50, failure to achieve endoscopic remission, and the presence of active extra-intestinal manifestations in both diseases. Disease monitoring with imaging and/or endoscopy during the previous year was conducted in ∼50 % of patients, with endoscopy performed in ∼40 %. Potential therapeutic adjustments were reported for half of the patients. CONCLUSIONS: This study highlights SDC in a significant portion of IBD Italian patients. These results emphasize the need for more proactive management strategies in both CD and UC patients.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".