S114 Low-Dose Azathioprine After Sustained Clinical Remission in Small Bowel Crohn’s Disease: is Some Really Better Than Nothing?
Bibliographic record
Abstract
Background: Maintenance therapy with thiopurines is recommended in small bowel Crohn’s Disease (CD) patients who achieve clinical remission with these drugs. Nevertheless, dose reduction may be required. Currently, there are no available investigations directly comparing patients who remain with low-dose azathioprine (LDA) (< 2mg/kg) monotherapy and patients with no specific therapies (NST) after sustained clinical remission. Our aim was to directly compare the outcomes between LDA monotherapy and NST in this setting. Methods: Our investigation has retrospectively included patients with small bowel CD (Montreal classification L1±L4) in corticosteroid-free remission, who were previously medicated with azathioprine in monotherapy, and posteriorly LDA or NST. A minimal follow-up period of 24 months was required. Patients with previous biologic or surgical therapies were excluded. The measured outcomes were the probability of maintaining clinical (need for therapeutic step-up) and biochemical (C-reactive protein and fecal calprotectin) remission, as well as the occurrence of infections during the follow-up period. Results: Fifty patients were included, from which 17 (34%) were females, with a mean age of 43±11 years. From these, 29 (58%) were under NST for CD, while 21 (42%) were under LDA. No statistically significant differences were found regarding the need for therapeutic step-up (6.9% NST vs 9.5% LDA; p=0.564), as well as biochemical remission (C-reactive protein at 1 year p=0.901 and at 2 years p=0.618; fecal calprotectin at 1 year p=0.186 and at 2 years p=0.886) between the two groups. The incidence of infections was significantly higher in patients with LDA, not only for SARS-CoV-2 infection (52% vs 29%; p=0.025), prevalent throughout this period, but also for other infections (19% vs 0%; p=0.026). Conclusions: Monotherapy with low-dose azathioprine did not associate with better outcomes in small bowel CD patients in sustained remission, when compared to patients with no specific therapies. When there is a need for dose reduction, maintenance of this drug must be reconsidered, acknowledging the higher incidence of infections with no differences on the outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".