Drug Optimization in Patients with Mild-to-Moderate Ulcerative Colitis: A Global Survey
Bibliographic record
Abstract
Background/Objectives: The treatment of patients with mild-to-moderate ulcerative colitis (UC) is challenging. Although there are commonly used guidelines, therapy optimization is not standardized. We conducted a survey to investigate the management and treatment of patients with mild-to-moderate UC. Methods: Physicians with experience in treating inflammatory bowel diseases (IBD) were invited to participate in an anonymous, multiple-choice survey between June and July 2023. The survey addressed various issues of patient care such as patient monitoring, treatment optimization, follow-up, treatment decision making, and therapy de-escalation. Results: The survey included 222 physicians (59.9% men; mean age = 50.4 years) from 66 countries worldwide. Gastroenterologists were the most represented specialists (89.6%), followed by surgeons (3.2%), and internal medicine doctors (2.7%). Two-thirds of the participants (66.7%) had >10 years of experience in the field of IBD. The combination of oral (≥4 g/day) and rectal 5-aminosalicylic acid (5-ASA) was the preferred choice when optimizing therapy. Budesonide MMX (41.8%) and systemic steroids (39.9%) were preferred in patients who failed 5-ASA. Treatment decisions were predominantly based on endoscopic (99.0%) or clinical (59.8%) activity. A significant percentage of clinicians did not optimize therapy in the case of increased fecal calprotectin alone (45.1%) or radiological/ultrasound activity (39.8%) alone. Conclusions: The guidelines for the management of mild-to-moderate UC are well accepted in clinical practice. Endoscopic remission remains the main therapeutic target, followed by clinical remission. Fecal calprotectin and intestinal ultrasound still elicit complaints from physicians.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".