Probiotics for paediatric functional abdominal pain disorders: A rapid review
Bibliographic record
Abstract
Abstract Background Functional abdominal pain disorders (FAPD) are prevalent in the paediatric population, however, there is currently no consensus regarding best practices for treatment. The use of probiotics is becoming popular to treat FAPD. The goal of this rapid review is to synthesize the best evidence on the use of probiotics in children with FAPD. Methods Searches were conducted on five main databases. Randomized controlled trials (RCTs) of probiotic use in children (0 to 18 years) with FAPD were searched. Populations of interest were patients with functional abdominal pain (FAP), irritable bowel syndrome (IBS), and functional dyspepsia (FD), recruited based on Rome criteria. Outcomes of interest were changes in abdominal pain severity, frequency, and duration. Findings Eleven RCTs with 829 participants with the diagnosis of FAP (n=400), IBS (n=329), FD (n=45), and mixed population (n=55) were included. Of six studies of children with FAP, two (n=103) used Lactobacillus rhamnosus GG (LGG) and reported no significant effects on pain, and four (n=281) used Lactobacillus (L) reuteri DSM 17938, of which three (n=229) reported significant positive effects on either severity or frequency of pain. Of six trials of children with IBS, four (n=219) used LGG, of which three (n=168) reported a positive effect. One (n=48) used bifidobacteria and one used VSL #3 (n=59), both demonstrating positive effects with probiotics. Two studies of FD reported no benefit. No adverse events were attributed to probiotics. Conclusions There is preliminary evidence for use of probiotics, particularly LGG, in reducing abdominal pain in children with IBS. There are inconsistent positive effects of other probiotics, including L. reuteri DSM 17938, in reducing pain in patients with FAP, IBS, or FD. More RCTs with rigorous methodology using single or combination probiotics are warranted.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".