Probiotics for Celiac Disease: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
INTRODUCTION: Many patients with celiac disease (CD) experience persistent symptoms despite adhering to the gluten-free diet. Different studies have assessed the use of probiotics as an adjuvant treatment for CD. We performed a systematic review and meta-analysis to evaluate the efficacy of probiotics in improving gastrointestinal (GI) symptoms and quality of life (QOL) in patients with CD. METHODS: We searched EMBASE, MEDLINE, CINAHL, Web of Science, CENTRAL, and DARE databases up to February 2019 for randomized controlled trials (RCTs) evaluating probiotics compared with placebo for treating CD. We collected data on GI symptoms, QOL, adverse events, serum tumor necrosis factor-α, intestinal permeability, and microbiota composition. RESULTS: We screened 2,831 records and found that 7 articles describing 6 RCTs (n = 279 participants) were eligible for quantitative analysis. Probiotics improved GI symptoms when assessed by the GI Symptoms Rating Scale (mean difference symptom reduction: -28.7%; 95% confidence interval [CI] -43.96 to -13.52; P = 0.0002). There was no difference in GI symptoms after probiotics when different questionnaires were pooled. The levels of Bifidobacteria increased after probiotics (mean difference: 0.85 log colony-forming units (CFU) per gram; 95% CI 0.38-1.32 log CFU per gram; P = 0.0003). There were insufficient data on tumor necrosis factor-a levels or QOL for probiotics compared with placebo. No difference in adverse events was observed between probiotics and placebo. The overall certainty of the evidence ranged from very low to low. DISCUSSION: Probiotics may improve GI symptoms in patients with CD. High-quality clinical trials are needed to improve the certainty in the evidence (see Visual abstract, Supplementary Digital Content 2, http://links.lww.com/AJG/B595).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.093 | 0.027 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".