Enteral Feeding Therapy for Maintaining Remission in Crohn's Disease: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The efficacy of enteral nutrition (EN) for maintaining remission in patients with inactive Crohn's disease (CD) is unclear. The aim of this article was to systematically identify, review, and critically appraise the evidence on efficacy of EN in maintaining medically induced remission in CD. MATERIALS AND METHODS: Several databases were searched from inception to April 2015 for relevant citations of published randomized controlled trials and nonrandomized cohort studies. Two reviewers independently selected studies for inclusion and assessed study quality and risk of bias. The primary outcome was relapse rate in patients with inactive CD who have been in medically induced remission and subsequently started or maintained on EN. RESULTS: Twelve studies (1169 patients, including 95 children) fulfilled the inclusion criteria. As the included studies were significantly heterogeneous, a meta-analysis was not performed. Eleven studies showed that EN was either better than, or as effective as, the comparator in maintaining remission in patients with inactive CD. No major EN-related adverse events were reported. Only 1 adult randomized controlled trial (n = 51), with low risk of bias, compared EN with regular diet and found a relapse rate of 34% in the EN group versus 64% in the control group ( P < .01) after a mean follow-up of 11.9 months. CONCLUSIONS: EN is more effective than regular diet and as effective as some medications in maintaining remission for patients with inactive CD. Large, properly designed randomized controlled studies of sufficient duration are required to confirm this conclusion for EN versus individual medications.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".