The effects of resistant starches on inflammatory bowel disease in preclinical and clinical settings: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) is a debilitating chronic disease with limited treatment options. Resistant starches may represent a novel treatment for IBD. However, its efficacy and safety remain unclear. Our objective was to perform a systematic review to summarize the preclinical and clinical effects of resistant starch, which may help guide future studies. METHODS: Medline, EMBASE, and the Cochrane Central Register were searched. Included studies investigated the use of resistant starch therapy in in vivo animal models of IBD or human patients with IBD. Articles were screened, and data extracted, independently and in duplicate. The primary outcomes were clinical remission (clinical) and bowel mucosal damage (preclinical). RESULTS: 21 preclinical (n = 989 animals) and seven clinical (n = 164 patients) studies met eligibility. Preclinically, resistant starch was associated with a significant reduction in bowel mucosal damage compared to placebo (standardized mean difference - 1.83, 95% CI - 2.45 to - 1.20). Clinically, five studies reported data on clinical remission but clinical and methodological heterogeneity precluded pooling. In all five, a positive effect was seen in patients who consumed resistant starch supplemented diets. The majority of studies in both the preclinical and clinical settings were at a high or unclear risk of bias due to poor methodological reporting. CONCLUSIONS: Our review demonstrates that resistant starch is associated with reduced histology damage in animal studies, and improvements in clinical remission in IBD patients. These results need to be tempered by the risk of bias of included studies. Rigorously designed preclinical and clinical studies are warranted. Trial registration The review protocols were registered on PROSPERO (preclinical: CRD42019130896; clinical: CRD42019129513).
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 | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".