Impact of Probiotics on Children with Acute Gastroenteritis: Results from an Umbrella Meta-Analysis

Abstract

Background:

Probiotics have been suggested as therapeutic agents for acute gastroenteritis (AG) in children. However, the optimal probiotic strains, doses, and durations of supplementation remain unclear.

Objective:

This umbrella meta-analysis was conducted to assess the clinical efficacy of different strains of probiotics on AG.

Methods:

To gather pertinent evidence, a search was conducted on PubMed and Scopus from their inception up to October 12, 2025. Standardized mean difference and relative risk with their 95% confidence interval were used as the metrics for assessing treatment effects on continuous and binary outcomes, respectively.

Results:

A total of 36 eligible meta-analyses (MAs), including 107,541 participants, were included. The analysis showed that probiotics may help prevent the incidence of AG and decrease the duration of diarrhea, vomiting, fever, length of hospital stays, as well as the frequency of stool and the presence of diarrhea on specific days post-treatment. However, the effects were found to be strain-specific and, for certain outcomes, were influenced by the dose (colony-forming units) and duration of treatment. Overall, the most effective probiotics in terms of efficacy on AG symptoms were Saccharomyces boulardii CNCM I-745, Lacticaseibacillus rhamnosus GG (formerly Lactobacillus rhamnosus GG; ATCC 53103), Limosilactobacillus reuteri DSM 17938 (formerly Lactobacillus reuteri), Lactiplantibacillus acidophilus, Bacillus clausii O/C, Bifidobacterium animalis subsp. lactis BB-12 (formerly Bifidobacterium lactis), and a combination of Lactobacillus acidophilus spp.+ Bifidobacterium spp. Probiotics were effective in both viral and bacterial acute AG in inpatient and outpatient settings. The effects of probiotics on certain outcomes were dose- and duration-dependent, although these effects varied across strains and clinical settings.

Conclusions:

This study indicates that probiotics have the potential to prevent AG and reduce associated symptoms in children.

Keywords

acute gastroenteritis children diarrhea probiotics umbrella meta-analysis

Introduction

Acute gastroenteritis (AG) is a common diarrheal disease in children, characterized by inflammation of the gastrointestinal tract, often accompanied with symptoms such as vomiting, fever, nausea, and abdominal pain.¹ AG remains a major public health issue and is the fifth leading cause of mortality in children under five.² In addition, AG leads to high hospitalization rates and health care costs.³ AG can cause dehydration and electrolyte imbalances in children, leading to serious issues such as stunted growth, malnutrition, and impaired cognitive development.^4,5 AG in children is caused by various pathogens, including viruses (norovirus and rotavirus), protozoa, and bacteria.⁶ While many countries have recently implemented rotavirus vaccination, this preventive measure has not significantly reduced the burden of AG.⁷ Therefore, prioritizing effective management of AG remains crucial.

At present, the approach to managing childhood AG mainly emphasizes the use of oral rehydration salts (ORS) and ongoing nutritional support to prevent and treat dehydration.⁸ However, ORS cannot alleviate diarrheal symptoms and address gut microbiota dysbiosis.⁹ The disruption of intestinal microflora is a key characteristic of AG and its associated symptoms.¹⁰ Recently, there has been increasing interest in the use of probiotics as a potential complementary treatment.¹¹ Probiotics could boost host immunity, restore balance to intestinal microflora, and improve gut barrier function.¹² The current research on probiotics for AG in children has made significant progress, yet several potential gaps remain that warrant further investigation. Discrepancies exist regarding the overall effectiveness of different probiotics strains and formulations on AG. While some meta-analyses (MAs) indicate that probiotics can effectively reduce the duration of diarrhea and stool frequency,^13,14 several other MAs revealed minimal or no benefits.¹⁵ A recent large randomized clinical trial (RCT) in the USA involving 971 children aged 3 months to 4 years found no differences in outcomes, including diarrhea duration and daycare absence, between those receiving Lacticaseibacillus rhamnosus GG (formerly Lactobacillus rhamnosus GG; ATCC 53103; hereafter LGG) and a placebo over 5 days.¹⁶ Another RCT in Vietnam found that Lactobacillus acidophilus (e.g., ATCC 4356 or NCFM; hereafter L. acidophilus) administered at a dosage of 4 × 10⁸ colony-forming units (CFU) twice daily had no significant effect on the duration of diarrhea and stool frequency during the first three days after enrollment.¹⁷ In addition, the Cochrane Database of Systematic Reviews concluded that probiotics have minimal or no impact on the number of individuals experiencing diarrhea that lasts 48 h or more, and it remains unclear whether probiotics can shorten the duration of diarrhea. There were concerns about publication bias, significant heterogeneity in results, and potential biases in many studies included in the review.¹⁵

The inconsistency highlights the need for a comprehensive evaluation of the existing literature to clarify the overall impact of various strains of probiotics on AG outcomes in children. The most effective probiotic for children with AG remains controversial. Besides, the effectiveness of multi-strain probiotics compared to single strains is yet to be evaluated. Moreover, there is considerable variability in the dosages and durations of probiotic administration across studies, which complicates comparisons and generalizations. An umbrella MA serves as a valuable tool for synthesizing findings from multiple MAs, providing a higher level of evidence regarding the effectiveness of interventions. This umbrella MA was conducted to thoroughly investigate the effects of a wide range of single-strain and multi-strain probiotics, considering different doses and treatment durations, on AG in children. The aim was to identify the most effective probiotics, as well as the optimal dosage and treatment duration for managing AG in this population.

Materials and Methods

Search strategy

This report adheres to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses.¹⁸ To gather pertinent evidence, a search was conducted on PubMed and Scopus from their inception up to October 12, 2025. The primary search terms and MESH headings utilized for the search strategy are presented in Supplementary Table S1. The search was restricted to publications written in English. In addition, the reference lists of the identified MA were examined to find any other relevant research.

Inclusion criteria

Following the PICO framework, all pertinent MAs of RCTs that met the following criteria were included: Participants: Patients were children under 18 years old diagnosed with AG; Intervention: Probiotics administered at any dose, regardless of the strain; Comparator: Placebo; Outcomes: The primary outcome was the duration of diarrhea, while secondary outcomes included the length of hospitalization, length of fever, duration of vomiting, prevention of AG, presence of diarrhea on days 1 to ≥7, the frequency of diarrhea at various time points (days 1 to ≥7). We excluded letters, qualitative reviews, protocols, MA with unrelated interventions, abstracts, and proceedings from scientific conferences. Eligibility was assessed by two independent investigators, with the senior investigator resolving any disagreements between them.

Data extraction and quality assessment

Two investigators independently evaluated quality evaluation and extracted data using a standardized data extraction form, with any discrepancies resolved by consulting a third author. The following information was collected: author, year of publication, sample size, number of studies included, risk of bias assessment, effect sizes for outcomes, country, mean age, type of intervention, and dose and duration of treatment. If additional information was needed, the authors of the MA were contacted for further data. The methodological quality of the MA was assessed using the AMSTAR 2 tool, which comprises 16 items—7 of which are considered critical for determining the overall quality of a review. AMSTAR 2 categorizes reviews as “high,” “moderate,” “low,” or “critically low” quality.¹⁹

Calculating the overlap

Calculating overlap is essential in umbrella reviews since primary studies may appear in multiple MAs, which can bias results. Overlap was assessed visually through a citation matrix and quantified using three indices, including percentage of overlaps, covered area (CA), and corrected covered area (CCA) based on the following formulas:^20,21

% Overlaps = number of primary RCTs included in more than one MA/r

Covered area (CA) : \frac{N}{r c}

Corrected covered area (CCA) : \frac{N - r}{rc - r}

N: Total number of primary RCTs including duplicates

r: Number of rows or total number of primary RCTs

c: Number of columns or MAs

The overlap status was interpreted using the CCA score: values between 0 and 5 indicate a mild overlap, 6–10 signify a moderate overlap, 11–15 reflect a high overlap, and scores above 15 represent a very high degree of overlap.

Statistical analysis

Our analysis was based on pooling summary effect estimates from published MAs, not individual primary studies. This approach is consistent with the methodology used in previous umbrella reviews,^22–25 where the aim is to synthesize findings across multiple MAs rather than re-analyzing individual study data. Pooling effect sizes from MAs and pooling individual studies rely on the same fundamental statistical methods. Mean difference (MD) and 95% confidence interval (95% CI) were used as the metrics for assessing treatment effects on continuous outcomes. For binary outcomes, relative risk (RR) and 95% CI were employed. Data were combined using random-effects models suggested by DerSimonian and Laird.²⁶ The degree of heterogeneity among MA was evaluated using the I² test, with I² values exceeding 50% indicating a significant level of heterogeneity. When at least 10 effect sizes were available, publication bias was examined using Egger tests and funnel plots, where a p-value of less than 0.05 suggests the presence of publication bias. Sensitivity analysis was conducted by sequentially removing individual MAs to evaluate the impact of each study on the overall outcomes. Prespecified subgroup analyses were carried out based on quality of studies (low, moderate, and high), sample size (≥2000 vs. <2000 participants), etiology of disease (rotaviral, bacterial, nosocomial, and parasitic) type of probiotics, duration (≥6 vs. <6 days), dosage (≥10¹⁰ versus <10¹⁰ CFU), and symptom severity (inpatients vs. outpatients). In addition, meta-regression analysis was performed to determine whether the results were influenced by the number of included studies, sample size, and the proportion of primary studies with low risk of bias. Statistical analyses were conducted using STATA software (Version 15.1).

Results

Study selection

The literature search identified 491 citations, with 64 studies being duplicates. Following a thorough review of the titles and abstracts, 377 irrelevant citations were eliminated. A full-text evaluation of 50 potentially relevant studies led to the inclusion of 40 MAs in the analysis.^{13–15,22,27–62} The selection process is detailed in Figure 1. These 36 eligible MAs collectively provided 78 effect sizes associated with various probiotic interventions. The interventions examined included multi-strain probiotics in 15 MAs, Saccharomyces boulardii CNCM I-745 (S. boulardii) in 14 MAs, L. acidophilus in 8 MAs, LGG in 14 MAs, Lactobacillus spp. in 4 MAs, Bifidobacterium spp. in 2 MAs, a mixture of L. acidophilus spp.+ Bifidobacterium spp. in 3 MAs, Limosilactobacillus reuteri DSM 17938 (formerly Lactobacillus reuteri; hereafter L. reuteri) in 9 MAs, Bifidobacterium animalis subsp. lactis BB-12 (formerly Bifidobacterium lactis; hereafter B. lactis) in 2 MAs, Bacillus coagulans (formerly misclassified as Lactobacillus sporogenes) in 2 MAs, Bacillus clausii O/C (B. clausii) in 3 MAs, and Enterococcus faecium SF68 in 2 MAs (Table 1). The most commonly used probiotic strains were S. boulardii, L. acidophilus, LGG, and L. reuteri. The daily doses of probiotics varied from 0.02 × 10¹⁰ to 14.6 × 10¹⁰ CFU, with supplementation durations ranging from 3 to 105 days and a median follow-up period of 6 days. Sample sizes across the MA ranged from 304 to 13,443 participants, totaling 107,541 individuals. The number of primary studies included in each MA varied from 2 to 63, with a median of 18 studies. Bias in the primary studies was assessed using the Cochrane tool⁶³ or the Jadad scale,⁶⁴, revealing significant variability in the proportion of high-quality studies, ranging from 0% to 85% in each MA. For the duration of diarrhea, data were reported in 38 MA (76 effect sizes).^{13–15,22,27–41,44–62} Prevention of AG was assessed in 3 MAs (5 effect sizes).^42,43,53 Duration of hospitalization was reported in 20 MAs (32 effect sizes),^{13–15,28,31,33–38,40,41,44–47,52–58} and duration of vomiting in 7 MAs (12 effect sizes).^{13,37,38,41,45,49,58} Duration of fever was reported in 3 MAs (10 effect sizes).^13,41,58 Presence of diarrhea on specific days after treatment initiation were reported as follows: day 1 after treatment initiation in 6 MAs (6 effect sizes),^{14,34,43,45,53,59} day 2 in 12 MAs (21 effect sizes),^{13–15,31,43–45,49–51,53,59} day 3 in 21 MAs (29 effect sizes),^{14,15,28,31–35,38,43–47,49–53,58,59} day 4 in 13 MAs (15 effect sizes),^{14,28,31,32,38,43–45,47,49,52,53,59} day 5 in 7 MAs (7 effect sizes),^{14,31,43–45,50,53} day 6 in 4 MAs (4 effect sizes),^43,45,49,53 and day ≥7 in 7 MAs (7 effect sizes).^{31,44,45,49–51,53} Presence of stool frequency on specific days after treatment initiation were reported as follows: day 1 after treatment initiation in 9 MAs (11 effect sizes),^{14,29,31,36,38,40,41,45,49} day 2 in 11 MAs (22 effect sizes),^{13,14,28,29,31–33,38,45,54,59} day 3 in 11 MAs (13 effect sizes),^{14,28,29,31,32,34,38,40,45,49,58} day 4 in 6 MAs (6 effect sizes),^{14,29,31,40,45,49} day 5 in 3 MAs (3 effect sizes),^29,40,45 day 6 in 3 MAs (3 effect sizes),^31,45,49 and day ≥7 in 3 MAs (3 effect sizes).^31,45,49 According to AMSTAR-2 criteria, the quality assessment classified 12 MAs as high quality, 18 as moderate quality, and 6 as low quality. Table 1 summarizes the characteristics of the included MAs.

FIG. 1.

Flow diagram of the study.

Table 1.

Characteristics of Eligible Studies

Reference	Year	Country	No. studies	Sample size	Bias assessment, high-quality studies (n/total)	Age	Daily dose (CFU)	Duration of intervention (days)	Interventions	Outcomes	Quality
Szajewska⁴⁵	2020	Poland	29	4217	Cochrane tool, 7/29	1 month to 15 years	443 mg	NR	Saccharomyces boulardii	Duration of vomiting, duration of hospitalization, duration of diarrhea, presence of diarrhea on day 1, day 2, day 3, day 4, day 5, day 6, and day ≥ 7, stool frequency on day 1, day 2, day 3, day 4, day 5, day 6, and day ≥ 7	moderate
Di³⁰	2020	China	19	1624	NR	1 to 73 months	1.6 × 10¹⁰	6	Multi-strain probiotics Lactobacillus acidophilus	Duration of diarrhea	moderate
Szajewska⁵⁰	2013	Poland	15	2963	Cochrane tool, 0/15	NR	1.6 × 10¹⁰	NR	Lactobacillus GG	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 2, day 3, day 4, day 5, and day ≥ 7	moderate
Cheng²⁹	2022	China	15	1765	Cochrane tool, 2/15	12 to 22 months	0.5 × 10¹⁰	NR	Multi-strain probiotics Lactobacillus acidophilus, Lactobacillus spp. “Lactobacillus acidophilus spp.+ Bifidobacterium spp.”	Duration of diarrhea, stool frequency on day 1, day 2, day 3, day 4, and day 5	high
SZAJEWSKA	2006	Poland	5	619	Cochrane tool, 0/5	2 months to 12 years	470 mg	5	Saccharomyces boulardii	Duration of vomiting, duration of hospitalization, duration of diarrhea, presence of diarrhea on day 2, day 3, day 4, day 6, and day ≥ 7, stool frequency on day 1, day 3, day 4, day 6, and day ≥ 7	high
Szajewska⁵⁰	2013	Poland	5	352	Cochrane tool, 0/5	3 to 60 months	0.4 × 10¹⁰	5	Lactobacillus reuteri DSM 17,938	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 3	moderate
Szajewska⁵⁰	2013	Poland	4	304	Cochrane tool, 2/4	1 to 48 months	2.7 × 10¹⁰	3	Lactobacillus acidophilus	Duration of diarrhea, presence of diarrhea on day 3 and day 4	moderate
Salari⁴¹	2012	Iran	20	3867	Jadad scale, 17/20	NR	NR	14	Multi-strain probiotics	Duration of fever, duration of vomiting, duration of hospitalization, duration of diarrhea, stool frequency on day 1	low
Wu⁵⁷	2021	China	17	2861	Cochrane tool, 4/17	1 month to 14 years	0.6 × 10¹⁰	5	Multi-strain probiotics Lactobacillus GG Saccharomyces boulardii Lactobacillus reuteri DSM 17,938 Bifidobacterium lactis Lactobacillus sporogenes Lactobacillus acidophilus	Duration of hospitalization, duration of diarrhea,	moderate
Ahmadi²⁷	2015	Iran	14	1149	NR	1 to 72 months	1.3 × 10¹⁰	6	Multi-strain probiotics Lactobacillus GG	Duration of diarrhea	moderate
Ianiro³⁶	2018	Italy	6	1298	Cochrane tool, 4/6	6 months to 12 years	0.5 × 10¹⁰	5	Bacillus clausii	Duration of hospitalization, duration of diarrhea, stool frequency on day 1	moderate
Szajewska⁴⁴	2019	Poland	18	4208	Cochrane tool, 9/18	1 month to 7 years	1.6 × 10¹⁰	6	Lactobacillus GG	Duration of hospitalization, Duration of diarrhea, presence of diarrhea on day 2, day 3, day 4, day 5, and day ≥ 7	low
Malagon-Rojas	2020	Colombia	7	1740	Cochrane tool, 5/7	1 to 48 months	NR	46	Lactobacillus acidophilus	Duration of diarrhea	moderate
Sun⁴³	2023	China	9	963	Cochrane tool, 3/9	1 to 60 months	0.13 × 10¹⁰	13	Lactobacillus reuteri DSM 17,938	AG incidence, presence of diarrhea on day 1, day 2, day 3, day 4, day 5, and day 6	high
Dinleyici³¹	2012	Turkey	19	2588	Cochrane tool, NR	1 month to 12 years	562 mg	11	Saccharomyces boulardii	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 2, day 3, day 4, day 5, and day ≥ 7, stool frequency on day 1, day 2, day 3, day 4, day 6, and day ≥ 7	moderate
Szajewska⁴⁸	2009	Poland	7	944	NR	2 months to 12 years	250–750 mg	6	Saccharomyces boulardii	Duration of diarrhea	low
Urbaska	2016	Poland	8	1229	Cochrane tool, 6/8	1 month to 12 years	0.24 × 10¹⁰	48	Lactobacillus reuteri DSM 17,938	Duration of hospitalization, duration of diarrhea, AG incidence, presence of diarrhea on day 1, day 2, day 3, day 4, day 5, day 6, and day ≥ 7	moderate
Fu³⁴	2022	China	10	1282	Cochrane tool, 3/10	1 month to 12 years	NR	NR	Saccharomyces boulardii	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 1 and day 3, stool frequency on day 3	moderate
Feizizadeh³²	2014	Iran	22	2440	Cochrane tool, 4/22	2 month to 15 years	558 mg	6	Saccharomyces boulardii	Duration of diarrhea, presence of diarrhea on day 3 and day 4, stool frequency on day 2 and day 3	high
Patro Gołab	2019	Poland	4	347	Cochrane tool, 1/4	3 to 60 months	0.02 × 10¹⁰	6	Lactobacillus reuteri DSM 17,938	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 1, day 2, day 3, day 4, and day 5, stool frequency on day 1, day 2, day 3, and day 4	high
Sazawal⁴²	2006	USA	28	4844	Jadad scale, 13/34	NR	1.5 × 10¹⁰	23	Saccharomyces boulardii Lactobacillus GG Lactobacillus spp.	AG incidence	high
SZAJEWSKA⁵¹	2007	Poland	8	988	Cochrane tool, 3/8	1 to 36 months	0.85 × 10¹⁰	4	Lactobacillus GG	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 2, day 3, and day ≥ 7	high
Yang⁵⁸	2019	China	29	4911	Cochrane tool, NR	18 to 20 months	8.3 × 10¹⁰	NR	Multi-strain probiotics Saccharomyces boulardii Bifidobacterium spp. Lactobacillus spp.	Duration of fever, duration of vomiting, duration of hospitalization, duration of diarrhea, presence of diarrhea on day 3, stool frequency on day 3	moderate
Chmielewska⁵⁹	2008	Poland	2	106	NR	6 to 36 months	0.5 × 10¹⁰	5	Lactobacillus reuteri DSM 17,938	Duration of diarrhea, presence of diarrhea on day 1, day 2, day 3, and day 4, stool frequency on day 2	moderate
Higuchi	2023	Japan	14	1761	Cochrane tool, NR	NR	NR	NR	Multi-strain probiotics Enterococcus faecium Lactobacillus acidophilus Bifidobacterium spp.	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 3	low
McFarland⁴⁰	2021	USA	17	4059	Cochrane tool, 4/17	NR	9.6 × 10¹⁰	6	Multi-strain probiotics Bacillus clausii Lactobacillus GG Saccharomyces boulardii	Duration of hospitalization, duration of diarrhea, stool frequency on day 1, day 3, day 4, and day 5	high
Kambale³⁷	2020	Belgium	15	6986	Cochrane tool, NR	1 to 168 months	14.6 × 10¹⁰	105	Multi-strain probiotics	Duration of vomiting, duration of hospitalization, duration of diarrhea	moderate
Vecchio⁵⁶	2022	Italy	15	3465	NR	NR	NR	NR	Lactobacillus GG	Duration of diarrhea	low
Li¹³	2021	China	21	13443	Cochrane tool, NR	NR	NR	NR	Multi-strain probiotics Saccharomyces boulardii Lactobacillus GG Lactobacillus spp. Lactobacillus reuteri DSM 17,938 Lactobacillus acidophilus Bacillus clausii E. faecium Bifidobacterium lactis Lactobacillus sporogenes “Lactobacillus acidophilus spp.+ Bifidobacterium spp.”	Duration of fever, duration of vomiting, duration of hospitalization, duration of diarrhea, presence of diarrhea on day 2, stool frequency on day 2	low
Szajewska⁴⁶	2001	Poland	10	NR	Jadad scale, NR	1 to 48 months	1.3 × 10¹⁰	5	Multi-strain probiotics Lactobacillus GG Lactobacillus reuteri DSM 17,938 Lactobacillus acidophilus	Duration of diarrhea, presence of diarrhea on day 3	moderate
Van Niel	2001	USA	9	NR	NR	1 to 37 months	1.2 × 10¹⁰	4	“Lactobacillus acidophilus spp.+ Bifidobacterium spp.”	Duration of diarrhea, stool frequency on day 2	moderate
Li³⁸	2019	China	19	4073	Cochrane tool, NR	1 to 72 months	13.7 × 10¹⁰	6	Lactobacillus GG	Duration of vomiting, duration of hospitalization, duration of diarrhea, presence of diarrhea on day 3 and day 4, stool frequency on day 1, day 2, and day 3	high
Allen²⁸	2010	Philippines	63	6489	Cochrane tool, 33/63	Under 18 years	13.8 × 10¹⁰	6	Multi-strain probiotics Lactobacillus GG Saccharomyces boulardii	Duration of diarrhea, presence of diarrhea on day 3 and day 4, stool frequency on day 2 and day 3	high
Collinson	2019	UK	82	11526	Cochrane tool, 27/82	Under 18 years	1.7 × 10¹⁰	6	Multi-strain probiotics Lactobacillus reuteri DSM 17,938 Saccharomyces boulardii Lactobacillus GG	Duration of hospitalization, duration of diarrhea, presence of diarrhea on day 2 and day 3	high
Vassilopoulou⁵⁵	2021	Greece	19	3469	Cochrane tool, 8/20	1 month to 15 years	1.3 × 10¹⁰	5	Multi-strain probiotics	Duration of diarrhea	high
Florez³³	2018	Canada	28	4661	Cochrane tool, 15/28	2 months to 12 years	0.4 × 10¹⁰	5	Multi-strain probiotics Lactobacillus GG Saccharomyces boulardii	Duration of diarrhea, presence of diarrhea on day 3, stool frequency on day 2	moderate
Alsabri	2024	USA	19	5170	Cochrane tool, 18/25	6 months to 10 years	0.5 × 10¹⁰	NR	Multi-strain probiotics	Duration of diarrhea	moderate
Mcfarland⁶¹	2025	China	10	1125	Cochrane tool, 0/10	Under 18 years	125–500 mg	5	Saccharomyces boulardii	Duration of diarrhea	moderate
Michel⁶²	2025	Italy	11	2854	Cochrane tool, 4/11	NR	0.3 × 10¹⁰	3	Bacillus clausii	Duration of diarrhea	high
Minaz²²	2024	Pakistan	96	17236	Cochrane tool,34/96	From birth till 10 years	NR	NR	Multi-strain probiotics	Duration of diarrhea	moderate

AG, acute gastroenteritis; CFU, colony-forming unit; NR, not reported.

Overlap calculation

In the citation matrix (Supplementary Data S1), 40 MAs were arranged in columns, while 221 primary RCTs were presented in rows. Using the provided formulas, overlap metrics were calculated as follows:

Total number of primary RCTs including duplicates (N) = 828

Total number of RCTs (rows (r)) = 221

Number of MAs (columns (c)) = 40.

% Overlap = number of RCTs included in more than one MA/total number of RCTs = 136/221 = 61%

CA = N / (r \times c) = 828 / (221 \times 40) = 828 / 8840 = 0.0 9

CCA = \frac{N - r}{rc - r} = (828 - 221) / (8840 - 221) = 607 / 8619 = 0.0 7

The percentage overlap was 61%, the CA was 0.09, and the CCA was 0.07, reflecting a mild degree of overlap among primary studies across MAs. The CCA of 0.07 indicates that most primary studies were unique to individual MAs, ensuring that the results were not overly biased by duplicated data.

Quantitative synthesis

Incidence of AG

The results of the overall analysis and subgroup analysis based on the sample size, quality of MA, and dose and duration of treatment for all outcomes are presented in Table 2. A combined analysis of all the data indicated that probiotics did not significantly lower the risk of AG incidence. There was considerable heterogeneity among the MA (I² = 67.9%, p = 0.01) (Fig. 2). In the subgroup analysis, the risk of AG was reduced at higher doses of probiotics (≥10¹⁰ CFU), in MA with larger sample sizes, and particularly when LGG (RR = −0.89, 95% CI: −1.04, −0.74) was administered. However, no significant effects were noted for other types of probiotics (Fig. 2, Table 2).

FIG. 2.

Pooled analysis for the effect of probiotics on the incidence of acute gastroenteritis.

Table 2.

Overall and Subgroup Analyses for the Effect of Probiotics on Acute Gastroenteritis in Children

Outcomes	Subgroups	Effect sizes	Test of effect	Test of heterogeneity
Outcomes	Subgroups	Effect sizes	RR (95% CI)	I² (%)	P
Incidence of gastroenteritis	Overall	5	0.86 (0.61, 1.21)	67.9	0.014
Sample size	≥2000 participants	3	0.69 (0.55, 0.86)	0	0.557
Sample size	<2000 participants	2	1.26 (0.95, 1.68)	0	0.524
Daily dose (CFU)	≥10¹⁰	3	0.69 (0.55, 0.86)	2	0.557
Daily dose (CFU)	<10¹⁰	2	1.26 (0.95, 1.68)	0	0.524
Duration of supplementation	≥6 days	5	0.86 (0.61, 1.21)	67.9	0.014
Quality of studies	High	4	0.80 (0.52, 1.22)	73.4	0.010
Quality of studies	Moderate	1	1.11 (0.68, 1.81)	—	—
Presence of diarrhea on day 1	Overall	6	0.85 (0.72, 1.00)	82.6	0.001
Sample size	≥2000 participants	1	1.00 (0.97, 1.03)	—	—
Sample size	<2000 participants	5	0.75 (0.58, 0.96)	75.1	0.003
Daily dose (CFU)	<10¹⁰	4	0.79 (0.61, 1.03)	77.4	0.004
Daily dose (CFU)	NR	2	0.76 (0.39, 1.48)	77.9	0.033
Duration of supplementation (days)	≥6 days	3	0.23 (0.04, 1.42)	84.8	0.001
	<6 days	1	0.88 (0.79, 0.99)	—	—
	NR	2	0.76 (0.39, 1.78)	77.9	0.033
Quality of studies	High	2	0.36 (0.05, 2.91)	80.6	0.023
Quality of studies	Moderate	4	0.85 (0.69, 1.06)	83.3	0.021
Presence of diarrhea on day 2	Overall	21	0.52 (0.44, 0.61)	63.0	0.001
Sample size	≥2000 participants	15	0.59 (0.49, 0.70)	56.8	0.004
Sample size	<2000 participants	6	0.41 (0.29, 0.58)	60.4	0.027
Daily dose (CFU)	≥10¹⁰	5	0.66 (0.53, 0.82)	38.5	0.165
	<10¹⁰	5	0.45 (0.32, 0.63)	58.8	0.046
	NR	11	0.46 (0.34, 0.62)	68.3	0.039
Duration of supplementation (days)	≥6 days	8	0.59 (0.49, 0.71)	61.3	0.012
	<6 days	3	0.42 (0.25, 0.73)	57.3	0.096
	NR	10	0.39 (0.24, 0.64)	66.7	0.001
Quality of studies	High	7	0.56 (0.44, 0.72)	63.7	0.011
	Moderate	5	0.60 (0.48, 0.75)	72.5	0.006
	Low	9	0.31 (0.22, 0.45)	0	0.636
Presence of diarrhea on day 3	Overall	29	0.54 (0.48, 0.61)	70.7	0.001
Sample size	≥2000 participants	15	0.54 (0.47, 0.62)	59.8	0.002
Sample size	<2000 participants	14	0.55 (0.44, 0.68)	76.4	0.003
Daily dose (CFU)	≥10¹⁰	14	0.56 (0.46, 0.68)	75.5	0.003
	<10¹⁰	8	0.42 (0.29, 0.61)	60.2	0.014
	NR	5	0.60 (0.52, 0.71)	57.6	0.051
Duration of supplementation	≥6 days	11	0.54 (0.44, 0.66)	50.1	0.029
	<6 days	11	0.46 (0.32, 0.64)	85.2	0.002
	NR	7	0.60 (0.56, 0.66)	0	0.473
Quality of studies	High	11	0.56 (0.47, 0.67)	54.8	0.015
	Moderate	16	0.50 (0.41, 0.62)	78.8	0.003
	Low	2	0.69 (0.59, 0.81)	0	0.695
Presence of diarrhea on day 4	Overall	15	0.63 (0.53, 0.75)	64.4	0.001
Sample size	≥2000 participants	9	0.51 (0.42, 0.63)	39.5	0.105
Sample size	<2000 participants	6	0.77 (0.67, 0.89)	14.2	0.324
Daily dose (CFU)	≥10¹⁰	7	0.58 (0.45, 0.74)	63.9	0.011
	<10¹⁰	4	0.85 (0.71, 1.02)	5.1	0.368
	NR	4	0.54 (0.38, 0.77)	46.2	0.134
Duration of supplementation	≥6 days	10	0.60 (0.47, 0.78)	74.6	0
	<6 days	3	0.69 (0.58, 0.81)	0	0.445
	NR	2	0.70 (0.44, 1.13)	20	0.264
Quality of studies	High	8	0.58 (0.45, 0.75)	74.7	0.002
	Moderate	6	0.71 (0.58, 0.87)	24.3	0.252
	Low	1	1.07 (0.44, 2.61)	—	—
Presence of diarrhea on day 5	Overall	7	0.77 (0.55, 1.07)	83.1	0.001
Sample size	≥2000 participants	4	0.58 (0.26, 1.30)	86.8	0.001
Sample size	<2000 participants	3	0.98 (0.86, 1.12)	0	0.698
Daily dose (CFU)	≥10¹⁰	2	1.17 (0.77, 1.78)	0	1.000
	<10¹⁰	3	0.98 (0.86, 1.12)	0	0.698
	NR	2	0.29 (0.19, 1.43)	0	0.685
Duration of supplementation	≥6 days	5	0.82 (0.58, 1.16)	83.9	0.001
Duration of supplementation	NR	2	0.62 (0.17, 2.19)	88.1	0.004
Quality of studies	High	2	1.01 (0.86, 1.17)	0	0.560
	Moderate	4	0.56 (0.28, 1.13)	88.9	0.001
	Low	1	1.17 (0.65, 2.12)	—	—
Presence of diarrhea on day 6	Overall	4	0.68 (0.43, 1.09)	58.8	0.063
Sample size	≥2000 participants	1	0.48 (0.24, 0.96)	—	—
Sample size	<2000 participants	3	0.78 (0.49, 1.24)	46.3	0.155
Daily dose (CFU)	<10¹⁰	2	0.97 (0.85, 1.10)	0	0.579
Daily dose (CFU)	NR	2	0.48 (0.30, 0.80)	0	0.967
Duration of supplementation	≥6 days	2	0.97 (0.85, 1.10)	0	0.579
	<6 days	1	0.49 (0.24, 1.00)	—	—
	NR	1	0.48 (0.24, 0.96)	—	—
Quality of studies	High	2	0.54 (0.29, 0.99)	0	0.630
Quality of studies	Moderate	2	0.74 (0.38, 1.45)	73.9	0.050
Presence of diarrhea on day ≥7	Overall	7	0.35 (0.18, 0.70)	82.3	0.001
Sample size	≥2000 participants	4	0.31 (0.19, 0.50)	0	0.823
Sample size	<2000 participants	3	0.44 (0.15, 1.32)	82.3	0.003
Daily dose (CFU)	≥10¹⁰	2	0.25 (0.10, 0.63)	0	0.944
	<10¹⁰	2	0.55 (0.15, 2.04)	84	0.012
	NR	3	0.32 (0.20, 0.52)	0	0.673
Duration of supplementation	≥6 days	3	0.51 (0.21, 1.20)	85	0.001
	<6 days	2	0.25 (0.11, 0.55)	0	1.000
	NR	2	0.25 (0.11, 0.57)	0	0.943
Quality of studies	High	2	0.25 (0.11, 0.55)	0	1.000
Quality of studies	Moderate	4	0.46 (0.20, 1.04)	82.4	0.001
	Low	1	0.25 (0.09, 0.72)	—	—
Outcomes	Subgroups	Effect sizes	SMD (95% CI)	I² (%)	P
Stool frequency on day 1	Overall	11	−0.11 (−0.23, 0.01)	25.4	0.202
Sample size	≥2000 participants	7	−0.10 (−0.27, 0.07)	45.7	0.087
Sample size	<2000 participants	4	−0.20 (−0.38, −0.03)	0	0.963
Daily dose (CFU)	≥10¹⁰	4	−0.06 (−0.26, 0.13)	59.8	0.059
	<10¹⁰	3	−0.20 (−0.38, −0.02)	0	0.908
	NR	4	−0.25 (−0.54, 0.05)	0	0.514
Duration of supplementation	≥6 days	7	−0.12 (−0.30, 0.07)	46	0.085
	<6 days	2	−0.20 (−0.38, −0.02)	0	0.746
	NR	2	−0.12 (−0.48, 0.24)	0	0.567
Quality of studies	High	7	−0.07 (−0.22, 0.08)	29.6	0.202
	Moderate	3	−0.19 (−0.35, −0.03)	0	0.495
	Low	1	−0.80 (−2.04, 0.44)	—	—
Stool frequency on day 2	Overall	22	−0.72 (−0.85, −0.59)	0	0.711
Sample size	≥2000 participants	18	−0.69 (−0.82, −0.55)	0	0.956
Sample size	<2000 participants	4	−1.19 (−1.89, −0.49)	45.3	0.140
Daily dose (CFU)	≥10¹⁰	4	−0.80 (−1.11, −0.48)	24	0.267
	<10¹⁰	6	−0.91 (−1.32, −0.51)	0	0.476
	NR	12	−0.66 (−0.82, −0.49)	0	0.811
Duration of supplementation	≥6 days	6	−0.70 (−0.88, −0.53)	0	0.949
	<6 days	5	−1.20 (−1.64, −0.76)	0	0.481
	NR	11	−0.63 (−0.84, −0.41)	0	0.728
Quality of studies	High	6	−0.71 (−0.94, −0.48)	0	0.913
	Moderate	7	−0.90 (−1.21, −0.59)	22.3	0.259
	Low	9	−0.63 (−0.87, −0.40)	0	2.567
Stool frequency on day 3	Overall	13	−0.90 (−1.26, −0.54)	77.6	0.001
Sample size	≥2000 participants	9	−0.85 (−1.37, −0.34)	82.2	0.001
Sample size	<2000 participants	4	−0.92 (−1.27, −0.58)	27.4	0.248
Daily dose (CFU)	≥10¹⁰	5	−0.55 (−1.12, 0.02)	62.1	0.032
	<10¹⁰	2	−0.64 (−1.02, −0.27)	0	0.454
	NR	5	−1.40 (−1.66, −1.14)	23.2	0.267
Duration of supplementation	≥6 days	7	−0.87 (−1.57, −0.17)	85	0.001
	<6 days	1	−1.30 (−1.93, −0.67)	—	—
	NR	5	−0.82 (−1.08, −0.57)	6.4	0.370
Quality of studies	High	8	−0.72 (−1.13, −0.30)	56.8	0.023
Quality of studies	Moderate	5	−1.14 (−1.57, −0.70)	69.6	0.011
Stool frequency on day 4	Overall	6	−0.78 (−1.24, −0.32)	86.5	0.001
Sample size	≥2000 participants	3	−1.07 (−1.61, −0.52)	74.3	0.020
Sample size	<2000 participants	3	−0.51 (−1.03, 0.01)	78.2	0.001
Daily dose (CFU)	≥10¹⁰	1	−0.61 (−1.06, 0.16)	—	—
	<10¹⁰	2	−0.24 (−0.52, −0.03)	0	0.915
	NR	3	−1.28 (−1.49, −1.07)	0	0.715
Duration of supplementation	≥6 days	3	−0.75 (−1.44, −0.05)	91.5	0.001
	<6 days	1	−1.10 (−1.58, −0.62)	—	—
	NR	2	−0.70 (−1.78, 0.39)	77.2	0.036
Quality of studies	High	4	−0.53 (−0.91, −0.15)	68.5	0.023
Quality of studies	Moderate	2	−1.32 (−1.55, −1.09)	0	0.953
Stool frequency on day 5	Overall	3	−0.33 (−0.86, 0.19)	60.1	0.057
Sample size	≥2000 participants	3	−0.51 (−0.90, −0.11)	0	0.397
Sample size	<2000 participants	1	0.15 (−0.22, 0.52)	—	—
Daily dose (CFU)	≥10¹⁰	2	−0.59 (−1.24, 0.07)	40.2	0.196
	<10¹⁰	1	0.15 (−0.22, 0.52)	—	—
	NR	1	−0.85 (−2.51, 0.81)	—	—
Duration of supplementation	≥6 days	2	−0.59 (−1.24, 0.07)	40.2	0.196
Duration of supplementation	NR	2	−0.01 (−0.72, 0.71)	24.3	0.251
Quality of studies	High	3	−0.30 (−0.87, 0.28)	70.8	0.033
Quality of studies	Moderate	1	−0.85 (−2.51, 0.81)	—	—
Stool frequency on day 6	Overall	3	−0.83 (−2.12, 0.46)	89.7	0.001
Sample size	≥2000 participants	2	−0.07 (−0.31, 0.18)	0	0.372
Sample size	<2000 participants	1	−1.70 (−2.40, −1.00)	—	—
Quality of studies	High	1	−1.70 (−2.40, −1.00)	—	—
Quality of studies	Moderate	2	−0.07 (−0.31, 0.18)	0	0.372
Stool frequency on day ≥7	Overall	3	−0.84 (−1.15, −0.52)	0	0.608
Sample size	≥2000 participants	2	−0.79 (−1.21, −0.38)	0	0.346
Sample size	<2000 participants	1	−0.90 (−1.38, −0.42)	—	—
Quality of studies	High	1	−0.90 (−1.38, −0.42)	—	—
Quality of studies	Moderate	2	−0.79 (−1.21, 0.38)	0	0.346
Duration of diarrhea (days)	Overall	76	−0.83 (−0.98, −0.69)	90.7	0.001
Sample size	≥2000 participants	47	−0.94 (−1.05, −0.83)	65	0.01
Sample size	<2000 participants	29	−0.57 (−0.84, −0.29)	94.9	0.001
Daily dose (CFU)	≥10¹⁰	25	−0.82 (−0.97, −0.67)	76.6	0.001
	<10¹⁰	25	−0.73 (−1.17, −0.30)	95.7	0.001
	NR	23	−0.87 (−0.98, −0.76)	40.5	0.029
Duration of supplementation	≥6 days	23	−0.89 (−1.03, −0.76)	64.3	0.01
	<6 days	23	−0.93 (−1.14, −0.71)	84.3	0.001
	NR	30	−0.57 (−0.86, −0.27)	94.5	0.001
Quality of studies	Moderate	36	−0.86 (−1.00, −0.72)	83	0.001
Quality of studies	Low	19	−0.46 (−0.90, −0.01)	95.4	0.001
Duration of hospitalization (days)	Overall	32	−0.82 (−0.92, −0.18)	0	0.736
Sample size	≥2000 participants	24	−0.81 (−0.93, −0.69)	0	0.515
Sample size	<2000 participants	8	−0.84 (−1.03, −0.65)	0	0.830
Daily dose (CFU)	≥10¹⁰	10	−0.91 (−1.12, −0.70)	0	0.487
	<10¹⁰	6	−0.74 (−1.05, −0.42)	0	0.833
	NR	14	−0.86 (−1.02, −0.71)	0	0.991
Duration of supplementation	≥6 days	12	−0.91 (−1.09, −0.72)	0	0.559
	<6 days	5	−0.90 (−1.18, −0.62)	0	0.816
	NR	15	−0.75 (−0.89, −0.61)	0	0.581
Quality of studies	High	9	−0.89 (−1.10, −0.68)	0	0.480
	Moderate	12	−0.79 (−0.95, −0.63)	20	0.247
	Low	11	−0.82 (−1.08, −0.56)	0	0.956
Duration of vomiting (days)	Overall	12	−0.16 (−0.26, −0.07)	16	0.288
Sample size	≥2000 participants	11	−0.17 (−0.29, −0.06)	22	0.234
Sample size	<2000 participants	1	−0.10 (−0.34, 0.14)	—	—
Daily dose (CFU)	<10¹⁰	3	−0.16 (−0.46, 0.14)	70.8	0.033
Daily dose (CFU)	NR	9	−0.17 (−0.29, −0.06)	0	0.633
Duration of supplementation	≥6 days	3	−0.11 (−0.46, 0.24)	47.1	0.151
	<6 days	1	−0.10 (−0.34, 0.14)	—	—
	NR	8	−0.22 (−0.32, −0.11)	0	0.551
Quality of studies	High	2	−0.73 (−2.49, 1.04)	64.6	0.093
	Moderate	3	−0.20 (−0.43, 0.03)	71.4	0.030
	Low	7	−0.14 (−0.29, −0.01)	0	0.807
Duration of fever (days)	Overall	10	−0.20 (−0.33, −0.07)	0	0.938
Sample size	≥2000 participants	10	−0.20 (−0.33, −0.07)	0	0.938
Daily dose (CFU)	≥10¹⁰	1	−0.98 (−7.18, 5.22)	—	—
Daily dose (CFU)	NR	9	−0.20 (−0.33, −0.07)	0	0.899
Duration of supplementation	≥6 days	1	−0.18 (−0.34, −0.02)	—	—
Duration of supplementation	NR	9	−0.23 (−0.45, −0.02)	0	0.905
Quality of studies	Moderate	1	−0.98 (−7.18, 5.22)	—	—
Quality of studies	Low	9	−0.20 (−0.33, −0.07)	0	0.805

95% CI, 95% confidence interval; CFU, colony-forming unit; NR, not reported; RR, relative risk; SMD, standardized mean difference.

Duration of diarrhea

When all effect sizes were pooled, probiotics significantly reduced the duration of diarrhea (Standardized mean difference [SMD] = −0.83 days, 95% CI: −0.98, −0.69), which was supported across subgroups based on sample size, quality of MA, as well as dose and duration of treatment. This effect was found for multi-strain probiotics (SMD = −0.91, 95% CI: −1.10, −0.72), S. boulardii (SMD = −1.01, 95% CI: −1.13, −0.90), LGG (SMD = −0.99, 95% CI: −1.20, −0.78), Lactobacillus spp (SMD = −0.35, 95% CI: −0.64, −0.06), L. reuteri (SMD = −1.12, 95% CI: −1.29, −0.95), B. lactis (SMD = −2.55, 95% CI: −3.30, −1.80), and B. clausii (SMD = −0.40, 95% CI: −0.71, −0.08), of which B. lactis and L. reuteri showed the highest efficacy, respectively (Fig. 3, Table 2).

FIG. 3.

Pooled analysis for the effect of probiotics on the duration of diarrhea (day).

Overall and subgroup analyses were conducted to evaluate which strains and doses are most effective for viral and bacterial AG. All probiotics reduced the duration of rotaviral AG, with S. boulardii and Lactobacillus GG showing the highest efficacy, particularly at doses ≥10¹⁰ CFU. For bacterial AG, only S. boulardii at doses ≥10¹⁰ CFU was effective. L. reuteri DSM 17,938 was effective in reducing the duration of nosocomial AG. S. boulardii was also effective in AG of unknown cause but was not effective against parasitic AG (Table 3). When subgroup analysis was conducted based on symptom severity, probiotics were effective in reducing the duration of AG in both inpatient and outpatient settings. S. boulardii, B. clausii, and L. reuteri DSM 17,938 were the most beneficial strains for reducing the duration of AG in inpatients. For outpatients, Lactobacillus GG was the most effective strain, followed by multi-strain probiotics and S. boulardii. Subgroup analyses were conducted according to the dose of probiotics within both the inpatient and outpatient populations. The results indicated that the effect of probiotics in both subgroups was not influenced by the administered dose (Table 3).

Table 3.

Overall and Subgroup Analyses for the Effect of Probiotics on Duration of Acute Gastroenteritis Based on Etiology and Symptom Severity

	Subgroups	Effect sizes	Test of effect	Test of heterogeneity
	Subgroups	Effect sizes	SMD (95%CI)	I ² (%)	P
Etiology
Rotaviral	Overall	17	−1.00 (−1.26, −0.73)	87.3	0.001
	Multi-strain probiotics	5	−0.69 (−0.99, −0.39)	72.7	0.005
	Saccharomyces boulardii	3	−1.27 (−2.09, −0.46)	84.5	0.002
	Lactobacillus GG	7	−1.14 (−1.72, −0.56)	91.8	0.001
	Lactobacillus acidophilus	2	−0.67 (−0.92, −0.42)	63.6	0.032
Daily dose (CFU)	≥10¹⁰	8	−1.13 (−1.59, −0.68)	88.7	0.001
	<10¹⁰	5	−0.81 (−1.20, −0.42)	82.0	0.001
	NR	4	−0.98 (−1.62, −0.33)	88.6	0.001
Bacterial	Overall	6	−0.15 (−0.61, 0.30)	60.3	0.027
	Saccharomyces boulardii	2	−1.08 (−1.77, −0.39)	0.0	0.37
	Lactobacillus GG	4	0.16 (−0.13, 0.45)	0.0	0.76
Daily dose (CFU)	≥10¹⁰	2	−0.25 (−.11, −0.61)	0.0	0.49
	<10¹⁰	2	−0.001 (−0.49, 0.49)	0.0	0.84
	NR	2	−1.08 (−1.77, −0.39)	0.0	0.37
Nosocomial	Overall	1	−1.03 (−1.62, −0.45)	—	—
Nosocomial	Lactobacillus reuteri DSM 17,938	1	−1.03 (−1.62, −0.45)	—	—
Parasitic	Overall	1	−0.54 (−1.89, 0.81)	—	—
Parasitic	Saccharomyces boulardii	1	−0.54 (−1.89, 0.81)	—	—
Unknown cause	Overall	5	−0.92 (−1.13, −0.70)	0.0	0.95
	Saccharomyces boulardii	1	−0.91 (−1.29, −0.52)	—	—
	Lactobacillus GG	3	−0.23 (−1.33, −0.53)	0.0	0.72
	Lactobacillus acidophilus	1	−0.91 (−1.24, −0.58)	—	—
Symptom severity
Inpatients	Overall	12	−0.94 (−1.12, −0.77)	51.6	0.019
	Multi-strain probiotics	4	−0.76 (−0.87, −0.65)	0.0	0.47
	Saccharomyces boulardii	3	−1.10 (−1.59, −0.62)	76.3	0.015
	Lactobacillus GG	3	−0.71 (−1.14, −0.27)	0.0	0.83
	Bacillus clausii	1	−1.39 (−2.74, −0.04)	—	—
	Lactobacillus reuteri DSM 17,938	1	−1.35 (−1.71, −0.99)	—	—
Daily dose (CFU)	≥10¹⁰	8	−0.92 (−1.13, −0.70)	0.0	0.50
	<10¹⁰	2	−1.02 (−1.62, −0.41)	90.02	0.001
	NR	2	−.95 (−1.38, −0.52)	78.4	0.03
Outpatients	Overall	10	−1.13 (−1.44, −0.83)	63.0	0.004
	Multi-strain probiotics	4	−1.10 (−1.67, −0.53)	82.8	0.001
	Saccharomyces boulardii	3	−0.97 (−1.27, −0.67)	0.0	0.47
	Lactobacillus GG	3	−1.49 (−2.33, −0.64)	39.4	0.192
Daily dose (CFU)	≥10¹⁰	7	−1.21 (−1.71, −0.71)	72.0	0.002
	<10¹⁰	1	−1.21 (−1.50, −0.92)	—	—
	NR	2	−.86 (−1.23, −0.49)	0.0	0.47

95% CI, 95% confidence interval; CFU, colony-forming unit; SMD, standardized mean difference.

Duration of hospitalization

The overall effect size for hospitalization when comparing probiotics to placebo across all included data was −0.82 days (SMD = −0.82 days, 95% CI: −0.92, −0.72), which was supported across all subgroups. This effect was identified for multi-strain probiotics (SMD = −0.84, 95% CI: −1.03, −0.65), S. boulardii (SMD = −0.89, 95% CI: −1.04, −0.74), LGG (SMD = −1.07, 95% CI: −1.50, −0.63), L. reuteri (SMD = −0.73, 95% CI: −1.15, −0.30), and B. clausii (SMD = −0.73, 95% CI: −1.28, −0.18), of which LGG demonstrated the highest efficacy (Fig. 4, Table 2).

FIG. 4.

Pooled analysis for the effect of probiotics on duration of hospitalization (day).

Presence of diarrhea on various days after treatment initiation

The forest plots illustrating the effect of different probiotics on the presence of diarrhea from day 1 to day ≥7 after treatment initiation are presented in Supplementary Figures S1, S2, S3, S4, S5, S6, and S7. In the overall analysis, probiotics reduced the risk of diarrhea compared to placebo on day 2 (RR = 0.52, 95% CI: 0.44, 0.61), day 3 (RR = 0.54, 95% CI: 0.48, 0.61), day 4 (RR = 0.63, 95% CI: 0.53, 0.75), and day ≥7 (RR = 0.35, 95% CI: 0.18, 0.70) (Table 2). However, in the stratified analysis, the risk of diarrhea on day 1 was reduced in MA with <2000 participants (Table 2), but no strain-specific effect was identified (Supplementary Fig. S1). The presence of diarrhea on day 2 was significantly reduced after receiving S. boulardii (RR = 0.54, 95% CI: 0.40, 0.73), LGG (RR = 0.52, 95% CI: 0.34, 0.80), L. reuteri (RR = 0.42, 95% CI: 0.28, 0.61), and a combination of L. acidophilus spp.+ Bifidobacterium spp. (RR = 0.20, 95% CI: 0.05, 0.78) (Supplementary Fig. S2), which was supported across all other subgroups (Table 2). The odds of diarrhea on day 3 after treatment initiation was significantly deceased for multi-strain probiotics (RR = 0.61, 95% CI: 0.54, 0.69), S. boulardii (RR = 0.45, 95% CI: 0.35, 0.59), LGG (RR = 0.56, 95% CI: 0.46, 0.68), and L. reuteri (RR = 0.43, 95% CI: 0.30, 0.61) (Supplementary Fig. S3), a finding that was consistent across all other subgroups (Table 2). On day 4, the odds of diarrhea were also significantly decreased for multi-strain probiotics (RR = 0.41, 95% CI: 0.32, 0.53), S. boulardii (RR = 0.50, 95% CI: 0.37, 0.69), LGG (RR = 0.64, 95% CI: 0.50, 0.82), and L. acidophilus (RR = 0.69, 95% CI: 0.57, 0.83), although no significant effect was observed for L. reuteri (Supplementary Fig. S4). This finding was consistent across all subgroups except for low-quality MA and when the dose was less than <10¹⁰ CFU. On day 5, diarrhea was significantly reduced after treatment with S. boulardii (RR = 0.29, 95% CI: 0.19, 0.43), but not when LGG or L. reuteri were administered (Supplementary Fig. S5). High-quality MA involving ≥2000 participants demonstrated a significant positive effect of S. boulardii (RR = 0.48, 95% CI: 0.30, 0.80) on the presence of diarrhea on day 6, while no effect was observed for L. reuteri (Supplementary Fig. S6). Also, high-quality MA with ≥2000 participants showed a significant positive impact of S. boulardii (RR = 0.32, 95% CI: 0.20, 0.52) and LGG (RR = 0.25, 95% CI: 0.12, 0.50) on reducing the risk of diarrhea lasting for ≥7 days after treatment initiation (Supplementary Fig. S7) particularly when administered at a higher dose (≥10¹⁰ CFU) for a short duration (<6 days) (Table 2), while no effect was found for L. reuteri (Supplementary Fig. S7).

Stool frequency on various days after treatment initiation

The forest plots for the effect of different probiotics on stool frequencies on day 1 to day ≥7 after treatment initiation are presented in Supplementary Figures S8, S9, S10, S11, S12, S13, and S14. In the overall analysis, compared with placebo, probiotics reduced stool frequency on day 2 after treatment initiation (SMD = −0.72, 95% CI: −0.85, −0.59), on day 3 (SMD = −0.90, 95% CI: −1.26, −0.54), on day 4 (SMD = −0.78, 95% CI: −1.24, −0.32) and on day ≥7 (all MA used S. boulardii; SMD = −0.84, 95% CI: −1.15, −0.52), but not on days 1, 5, and 6 (Table 2). In the stratified analysis, MA of moderate quality with sample sizes under 2000 participants, doses below 10¹⁰ CFU, and intervention durations of <6 days indicated a significant reduction in stool frequency on day 1, but no strain-specific effect was observed (Supplementary Fig. S8). On day 2, stool frequency significantly decreased following the administration of multi-strain probiotics (SMD = −0.83, 95% CI: −1.14, −0.51), S. boulardii (SMD = −0.68, 95% CI: −0.88, −0.48), LGG (SMD = −0.64, 95% CI: −0.95, −0.33), L. reuteri (SMD = −1.55, 95% CI: −2.15, −0.95), and L. acidophilus spp.+ Bifidobacterium spp. (SMD = −1.15, 95% CI: −1.94, −0.35) (Supplementary Fig. S9). This reduction was consistent regardless of the dose and duration of the intervention. On day 3, stool frequency also significantly decreased with multi-strain probiotics (SMD = −0.80, 95% CI: −1.20, −0.40), S. boulardii (SMD = −1.36, 95% CI: −1.62, −1.10), and L. acidophilus (SMD = −0.61, 95% CI: −1.00, −0.22) (Supplementary Fig. S10). Notably, this effect was significant only when lower doses of probiotics were used. On day 4, a significant reduction in stool frequency was observed specifically for the subgroup receiving S. boulardii (SMD = −1.08, 95% CI: −1.45, −0.71) (Supplementary Fig. S11), particularly at higher doses (≥10¹⁰ CFU). In addition, MA involving at least 2000 participants indicated that probiotics could reduce stool frequency on day 5, while high-quality MA showed a significant decrease in stool frequency on day 6 as well. Subgroup analyses further supported the beneficial impact of probiotics on stool frequency ≥day 7 after treatment initiation (Table 2).

Duration of vomiting

The overall effect size for vomiting when comparing probiotics to placebo was −0.16 day (SMD = −0.16, 95% CI: −0.26, −0.07). Subgroup analyses based on the type of probiotics did not support this effect (Supplementary Fig. S15), although it was supported by MA involving ≥2000 participants, as well as by low-quality MA (Table 2).

Duration of fever

The overall analysis for vomiting found that probiotics significantly decreased the duration of fever (SMD = −0.20, 95% CI: −0.33, −0.07). Subgroup analyses based on the type of probiotics showed a positive effect only when multi-strain probiotics (SMD = −0.18, 95% CI: −.04, −0.33) were used (Supplementary Fig. S15). Subgroup analysis by sample size, dose, duration of treatment, and quality of MA supported this finding (Table 2).

Sensitivity analysis and publication bias

There was a significant publication bias observed for diarrhea on days 2 and 3 after treatment initiation, as well as for stool frequency on day 1 after treatment initiation (Fig. 5). In contrast, other outcomes did not show any evidence of publication bias. In the sensitivity analysis, the pooled effect size for the incidence of AG was influenced by the study conducted by Sun et al.⁴³ The presence of diarrhea on day 1 was impacted by Szajewska et al.,⁴⁵ while the presence of diarrhea on day 6 was affected by Urbanska.⁵³ In addition, stool frequency on day 1 was influenced by McFarland et al.,⁴⁰ which diminished the reliability of the associated findings. When we excluded the MAs with the highest overlap (≥50% overlap) with other included MAs, the results remain consistent, showing the reliability of the findings.

FIG. 5.

Publication bias for the presence of diarrhea on day 2 (A), the presence of diarrhea on day 3 (B), and tool frequency on day 1 (C).

Meta-regression analysis

The effect of probiotics on the presence of diarrhea on day 4 was affected by sample size (B = −0.0001, SE = 0.0002, p = 0.01) and the dose of intervention (B = −0.004, SE = 0.0008, p = 0.001). For the presence of diarrhea on day ≥7, the pooled estimate was significantly affected by the duration of treatment (B = 0.02, SE = 0.005, p = 0.01) and the proportion of high-quality studies in each MA (B = 0.02, SE = 0.006, p = 0.02).

Safety and adverse effects

Generally, no adverse effects were reported in the probiotics and control groups.^{34,35,39,44,46,47,49,57} Urbanska et al.⁵³ reported that administration of Lactobacillus reuteri may result in a change in bowel habits, but Chmielewska et al.⁵⁹ showed that adverse effects associated with L. reuteri were not reported in any of the RCTs. Ianiro et al.³⁶ reported that vomiting was the most commonly reported adverse event after supplementation with B. clausii; however, no statistically significant difference in the number of patients experiencing adverse events was observed between the probiotic and placebo groups. In the MA by Schnadower et al.,¹⁶ some adverse events such as abdominal cramps, intestinal rumbling, nausea, weakness, bloating, constipation, loss of appetite, headache, and fever were reported in both the LGG and placebo groups, but no significant differences were observed between the trial groups in the rates of adverse events.

Discussion

This umbrella MA, which included 36 MA encompassing 78 probiotic interventions, suggested that probiotics may decrease the duration of diarrhea, the number of diarrheal episodes, presence of diarrhea, vomiting, fever, and the length of hospital stays in children. However, the effects were found to be strain-specific and, for certain outcomes, were influenced by the dose and duration of treatment. Moreover, there was weak evidence in subgroup analysis indicating that probiotics may help prevent the incidence of AG when LGG is prescribed at higher doses.

Several probiotics have been evaluated for their efficacy for preventing and treating AG, but have yielded inconsistent results. In this study, a higher dose of probiotics was effective in reducing the risk of diarrhea on day 4 and for diarrhea lasting ≥7 days when administered for a short duration of <6 days. Conversely, lower doses of probiotics were found to be more effective in decreasing stool frequency on days 1, 3, and 4. In addition, an intervention duration of less than <6 days was beneficial for reducing stool frequency on day 1, while longer intervention periods did not yield effective results. These findings suggest that both the dosage and duration of probiotic treatment play crucial roles in their effectiveness, indicating that tailored approaches may be necessary to optimize outcomes in different contexts.

For the duration of diarrhea, strains such as B. lactis and L. reuteri demonstrated the highest efficacy in reducing diarrhea duration, while multi-strain probiotics, S. boulardii, LGG, Lactobacillus spp, and B. clausii also showed positive effects. In terms of hospitalization duration, LGG was particularly effective, while multi-strain probiotics, S. boulardii, LGG, L. reuteri, and B. clausii also showed positive effects. Regarding the presence of diarrhea and the frequency of stools, generally, S. boulardii was the most beneficial intervention, indicating consistent positive effects through day 1 to ≥7 post-treatment. However, other strains such as LGG, L. reuteri, a combination of L. acidophilus spp.+ Bifidobacterium spp., L. acidophilus, and multi-strain probiotics also displayed positive impacts on specific days after the treatment. The strain-specific effects on AG symptoms are evident, with S. boulardii demonstrating superior efficacy over bacterial strains. This superiority likely arises from its yeast cell wall rich in β-1,3-glucans and mannoproteins, conferring exceptional gastric acid and bile tolerance compared to bacterial peptidoglycan walls, enabling direct binding to bacterial toxins (e.g., E. coli LT/ST) and competitive exclusion of pathogens in the inflamed gut.^65–67 S. boulardii also exhibits distinct phenotypic and physiological attributes that drive its probiotic efficacy, including optimal growth at body temperature, gastric acid resistance, and viability in low-pH conditions.⁶⁸ L. reuteri was effective in reducing the risk of diarrhea up to 3 days after the initiation of the intervention, but not after a longer duration of follow-up. Overall, these findings highlight the importance of strain selection and dosage in utilizing probiotics for managing AG symptoms in children, emphasizing that specific strains can have varying degrees of effectiveness in alleviating symptoms and shortening recovery time.

Given the strain-specific effects observed, health care providers can tailor probiotic use based on specific strains known to be effective for particular outcomes, enhancing treatment efficacy. Overall, the most effective probiotics in terms of efficacy on AG symptoms were S. boulardii, LGG, L. reuteri, L. acidophilus, B. clausii, B. lactis, and a combination of L. acidophilus spp.+ Bifidobacterium spp, which is consistent with existing evidence.^29,44,45,62

A MA found that B. clausii effectively reduced diarrhea, stool frequency, and hospital stay duration.⁶² Another MA by Cheng et al.²⁹ showed that L. acidophilus shortened diarrhea duration, although this effect was not statistically significant when used as a single strain. However, it was effective when administered at doses ≥0.01 × 10¹⁰ CFU daily, notably reducing diarrhea frequency between days 2 and 5, with significance on day 3. Szajewska et al.⁴⁴ reported that Lactobacillus rhamnosus GG did not affect stool volume compared to placebo but was associated with decreased hospitalization length and diarrhea duration at doses ≥10¹⁰ CFU. Moreover, S. boulardii reduced diarrhea duration, hospitalization time, and the risk of diarrhea from days 2 to 7.⁴⁵ These findings support the results of the current umbrella MA.

Both single-strain and multi-strain probiotics have demonstrated efficacy in reducing the duration of AG, but the choice depends on the clinical scenario. Our MA showed that specific single strains such as S. boulardii and Lactobacillus GG have strong evidence of benefit, particularly for bacterial and viral AG. Multi-strain probiotics also significantly reduce diarrhea duration and may offer a broader spectrum of activity, which could be advantageous in viral or mixed infections. Dose and treatment duration are critical, with higher doses (≥10¹⁰ CFU) showing greater efficacy in both viral and bacterial AG. The superior efficacy observed at higher doses likely reflects a functional persistence threshold rather than permanent colonization. Preclinical studies and select human trials demonstrate dose-dependent fecal recovery and mucosal interaction, often in the range of 10⁹–10¹⁰ CFU, which may be required to overcome gastrointestinal transit and dilution effects.⁶⁹ At these doses, probiotic exposure is sufficient to engage innate immune signaling pathways, including Toll-like receptor 2 (TLR2/MyD88)-mediated responses and anti-inflammatory cytokine production (e.g., IL-10^70,71 Higher CFU levels may also enhance pathogen suppression through increased antimicrobial metabolite production and competitive niche exclusion, with several clinical trials reporting improved outcomes in AG.^72,73 However, these effects are strain-specific and may exhibit dose plateaus rather than linear responses. Therefore, clinicians might prefer single strains with proven strain-specific benefits for targeted infections and consider multi-strain formulations for broader coverage, especially when the etiology is uncertain. Patient factors, availability, and safety profiles should also guide the decision. This evidence supports the integration of probiotics into clinical practice as a complementary approach alongside standard treatments like rehydration therapy, particularly for children at risk of severe dehydration and prolonged illness. However, clinicians should remain mindful of the variations in dose and duration that influence these outcomes, ensuring that probiotic administration is optimized for individual patient needs.

New insights of our study include dose-dependent effects and strain-specific impacts varying by viral or bacterial etiology. For example, S. boulardii was effective against bacterial AG and AG of unknown cause but not parasitic AG. These results support targeted probiotic use, aligning with previous findings while clarifying strain- and dose-specific responses that guide clinical application. This study further clarifies probiotic effects by subgroup analyses on symptom severity and health care settings, revealing distinct strain benefits in inpatient versus outpatient contexts. Such a nuanced evaluation extends prior research by linking probiotic effects to clinical variables, thus advancing practical understanding and optimizing therapeutic strategies in AG treatment. Overall, probiotics had no significant adverse effect compared to placebo, showing its safety in clinical practice. Altered bowel habits after L. reuteri use are typically transient and linked to microbiota shifts, such as enhanced short-chain fatty acid (SCFA) production.⁷⁴ However, in immunocompromised cases, rare bacteremia/fungemia risks (<0.01%) exist with S. boulardii, particularly in ICU settings with catheters.^75,76

Mechanistically, probiotics suggest several pathways, including competitive exclusion of pathogens, enhancement of gut barrier function, modulation of immune responses, and restoration of healthy gut microbiota, through which these interventions exert their beneficial effects on children with AG.⁷⁷ Probiotics enhance gut health by adhering to the intestinal mucosa, which helps create a protective barrier against pathogenic bacteria through competitive exclusion.⁷⁸ This adherence also stimulates the growth of beneficial commensal bacteria while inhibiting the proliferation of harmful pathogens, thereby reducing inflammation and promoting a favorable gut environment.⁷⁹ Furthermore, probiotics modulate the immune response by interacting with intestinal epithelial cells and immune cells, leading to the production of immunoglobulin A (IgA) and various cytokines that bolster mucosal immunity, which helps control infections.⁸⁰ S. boulardii has been shown to decrease inflammation in the gut by producing a low-molecular-weight soluble factor that inhibits Nuclear factor kappa B (NF-κB) activation and ERK1/2 MAP kinase signaling. This leads to decreased expression of the interleukin-8 (IL-8) and tumor necrosis factor alpha (TNF-α) genes, along with increased levels of anti-inflammatory cytokines such as IL-10 and an elevated IL-10/IL-12 ratio in intestinal epithelial cells and monocytes, resulting in reduced secretion of proinflammatory cytokines, thereby helping to reduce inflammation in conditions like AG.⁸¹ S. boulardii has been also demonstrated to attach to invading pathogens such as E. coli and Salmonella typhimurium through lectin receptors on its cell wall, which prevents these microbes from adhering to the intestinal brush border. This action helps trap the pathogens and facilitates their removal from the body during bowel movements.⁸² The synthesis of antimicrobial compounds, such as bacteriocins, cathelicidins, defensins, and SCFAs, further contributes to pathogen inhibition and promotes gut integrity.⁸³ L. acidophilus produces lactic acid and other metabolites that inhibit pathogen growth, thereby reducing diarrhea incidence.⁸⁴ LGG enhances the intestinal barrier by reinforcing tight junctions between epithelial cells and increasing the production of intestinal mucins. It also protects against damage triggered by lipopolysaccharide (LPS) or TNF-α, counteracting the reduction of essential barrier proteins such as mucin 2 (MUC2) and zonula occludens-1 (ZO-1), thereby maintaining the overall integrity of the intestinal lining.⁸⁵ LGG and B. lactis modulate immune responses by reducing the production of inflammatory cytokines such as TNF-α.^86,87 L. reuteri also enhances local immune responses and may reduce the severity and duration of diarrhea episodes by modulation of TLR4 and NF-κB signaling in the intestine.⁸⁸ The combination of L. acidophilus spp. + Bifidobacterium spp. leverages the strengths of both strains, enhancing overall efficacy in restoring gut microbiota balance and improving immune responses against pathogens.⁸⁹ As a spore-forming probiotic, B. clausii can survive harsh gastrointestinal conditions, allowing it to effectively colonize the gut and exert its beneficial effects.⁹⁰ It helps restore the balance of gut microbiota disrupted by infections or antibiotics, thus aiding recovery from diarrhea.⁹¹ These mechanisms highlight the potential of probiotics not only to prevent AG but also to alleviate its associated symptoms effectively.

Although several outcomes reached statistical significance, statistical significance does not necessarily imply clinical relevance. Some of the observed effect sizes, particularly for outcomes such as duration of vomiting and fever, were relatively small and may translate into modest absolute reductions in symptom duration. Therefore, the clinical importance of these findings should be interpreted with caution. In contrast, reductions in the duration of diarrhea and length of hospitalization may have greater practical implications, especially in moderate to severe cases or in resource-limited settings. In addition, this umbrella MA did not formally assess cost-effectiveness. While probiotics appear to confer clinical benefits in specific contexts, their economic value should be evaluated in future studies that incorporate cost analyses alongside clinical outcomes. Consequently, treatment decisions should consider not only statistical significance but also clinical magnitude of effect, patient characteristics, disease severity, and health care costs.

This study is the first umbrella MA to investigate the effects of probiotics on AG in children. A significant strength of this analysis is its comprehensive subgroup analysis based on the type of probiotics, as well as the dosage and duration of treatments, which aids in identifying sources of heterogeneity. In addition, meta-regression analysis was performed to further explore these sources of heterogeneity, and the reliability of the findings was evaluated through sensitivity analyses. The large sample size of 107,541 participants provided ample statistical power to detect effects. However, some limitations should be considered when interpreting these results. Significant heterogeneity was observed in certain outcomes across the MA, with meta-regression and stratified analyses indicating that differences in treatment dosage, probiotic types, treatment duration, study quality, sample size, and the proportion of studies with low bias contributed to this heterogeneity. Moreover, we found that variations in the etiology and severity of AG contributed significantly to the observed heterogeneity for diarrhea duration. Regional differences in gut microbiota composition can also influence host responses and susceptibility, thereby contributing to observed heterogeneity across the studies. Consequently, we employed random-effects models in our MA to yield more reliable summary estimates. In addition, caution is warranted when interpreting pooled findings for specific outcomes, particularly those derived from subgroup analyses due to the limited number of MAs involved. Furthermore, significant publication bias was identified for diarrhea on days 2 and 3, as well as for stool frequency on day 1. The search strategy focused solely on English publications, which may have led to the omission of some relevant MAs. Publication bias in our study likely arises because studies with positive or significant results are more frequently published than those with negative or null outcomes. This selective publication can lead to an overestimation of treatment effects and may distort the overall conclusions drawn from the analysis. Thus, the findings should be interpreted with caution. As this field continues to evolve rapidly, future research could enhance understanding by integrating results based on intervention and outcome characteristics, potentially resolving some existing uncertainties. Lastly, the literature search was restricted to two electronic databases (PubMed and Scopus). Although these databases provide extensive coverage of biomedical and multidisciplinary peer-reviewed literature, the exclusion of other databases such as Embase, Web of Science, and the Cochrane Library may have resulted in the omission of some potentially eligible MAs.

Conclusion

This study indicates that probiotics have the potential to prevent AG and reduce associated symptoms in children. However, it is important to note that these effects are strain-specific and may vary based on the dosage and duration of treatment, highlighting the need for careful consideration in probiotic selection and administration.

Statement of Ethics

As this study was a review of published literature, no ethics approval by a Research Ethics Board was required to conduct our research.

Authors’ Contributions

S.F., X.M., and R.L.: Investigation. S.F., X.M., and R.L.: Methodology. X.M.: Resources. X.M. and R.L.: Data curation. R.L.: Software. S.F. and X.M.: Writing—original draft. R.L.: Writing—review and editing. R.L.: Supervision.

Statement of Artificial Intelligence (AI) Use

Generative AI tools were employed solely to improve the English language quality of the article, using the Perplexity platform (https://www.perplexity.ai) under strict human supervision and review to ensure accuracy and clarity.

Footnotes

Author Disclosure Statement

The authors have no conflicts of interest to declare.

Funding Information

No sources of external funding were utilized for this project.

Supplemental Material

References

1. Florez

, Nino-Serna

, Beltran-Arroyave

. Acute infectious diarrhea and gastroenteritis in children. Curr Infect Dis Rep 2020;22(2):4; doi: 10.1007/s11908-020-0713-6

2. Guarino

, Aguilar

, Berkley

, et al. Acute gastroenteritis in children of the world: What needs to be done? J Pediatr Gastroenterol Nutr 2020;70(5):694–701; doi: 10.1097/MPG.0000000000002669

3. Barker

, Zomer

, O’Toole

, et al. Cost of gastroenteritis in Australia: A healthcare perspective. PLoS One 2018;13(4):e0195759; doi: 10.1371/journal.pone.0195759

4. Kumari

, Kumar

, Sharma

. Acute gastroenteritis: Its causes, maintenance, and treatment. J Pharm Negat Results 2022;13(8):5064–5078; doi: 10.47750/pnr.2022.13.S08.666

5. Pinkerton

, Oriá

, Lima

, et al. Early childhood diarrhea predicts cognitive delays in later childhood independently of malnutrition. Am J Trop Med Hyg 2016;95(5):1004–1010; doi: 10.4269/ajtmh.16-0150

6. Moro

, David

. Infectious gastroenteritis: Causes, diagnosis, treatment, and prevention. Curr Trends Gastroenterol Hepatol 2019;2(5):194–197; doi: 10.32474/CTGH.2019.02.000147

7. Troeger

, Blacker

, Khalil

, et al. Estimates of the global, regional, and national morbidity, mortality, and aetiologies of diarrhoea in 195 countries: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Infect Dis 2018;18(11):1211–1228; doi: 10.1016/S1473-3099(18)30362-1

8. Pieścik‐Lech

, Shamir

, Guarino

, Szajewska

. The management of acute gastroenteritis in children. Aliment Pharmacol Ther 2013;37(3):289–303; doi: 10.1111/apt.12163

9. Harrell

, Cheng

. Inability to reduce morbidity of diarrhea by ORS: Can we design a better therapy? Pediatr Res 2018;83(3):559–563; doi: 10.1038/pr.2017.295

10.

10. Castaño-Rodríguez

, Underwood

, Merif

, et al. Gut microbiome analysis identifies potential etiological factors in acute gastroenteritis. Infect Immun 2018;86(7):e00060; doi: 10.1128/IAI.00060-18

11.

11. Szajewska

, Guarino

, Hojsak

, et al.; European Society for Pediatric Gastroenterology, Hepatology, and Nutrition. Use of probiotics for management of acute gastroenteritis: A position paper by the ESPGHAN working group for probiotics and prebiotics. J Pediatr Gastroenterol Nutr 2014;58(4):531–539; doi: 10.1097/MPG.0000000000000320

12.

12. Krishna Rao

, Samak

. Protection and restitution of gut barrier by probiotics: Nutritional and clinical implications. Curr Nutr Food Sci 2013;9(2):99–107; doi: 10.2174/1573401311309020004

13.

13. Li

, Zhu

, Li

, et al. Which probiotic is the most effective for treating acute diarrhea in children? A Bayesian network meta-analysis of randomized controlled trials. Nutrients 2021;13(12):4319; doi: 10.3390/nu13124319

14.

14. Patro-Gołąb

, Szajewska

. Systematic review with meta-analysis: Lactobacillus reuteri DSM 17938 for treating acute gastroenteritis in children. An update. Nutrients 2019;11(11):2762; doi: 10.3390/nu11112762

15.

15. Collinson

, Deans

, Padua-Zamora

, et al. Probiotics for treating acute infectious diarrhoea. Cochrane Database Syst Rev 2020;12(12):CD003048; doi: 10.1002/14651858.CD003048.pub4

16.

16. Schnadower

, Tarr

, Casper

, et al. Lactobacillus rhamnosus GG versus placebo for acute gastroenteritis in children. N Engl J Med 2018;379(21):2002–2014; doi: 10.1056/NEJMoa1802598

17.

17. Hong Chau

, Minh Chau

, Hoang Le

, et al.; Oxford-Vietnam Probiotics Study Group. A double-blind, randomized, placebo-controlled trial of Lactobacillus acidophilus for the treatment of acute watery diarrhea in Vietnamese children. Pediatr Infect Dis J 2018;37(1):35–42; doi: 10.1097/INF.0000000000001712

18.

18. Brennan

, Munn

. PRISMA 2020: A reporting guideline for the next generation of systematic reviews. JBI Evid Synth 2021;19(5):906–908; doi: 10.11124/JBIES-21-00112

19.

19. Lu

, Lu

, Ge

, et al. Use of AMSTAR-2 in the methodological assessment of systematic reviews: Protocol for a methodological study. Ann Transl Med 2020;8(10):652; doi: 10.21037/atm-20-392a

20.

20. Hennessy

, Johnson

. Examining overlap of included studies in meta‐reviews: Guidance for using the corrected covered area index. Res Synth Methods 2020;11(1):134–145; doi: 10.1002/jrsm.1390

21.

21. Majidinia

, Shirazi

, Boruziniat

, Riahi

. Effect of low-and high-level laser therapy on the treatment of dentin hypersensitivity: An umbrella review. J Lasers Med Sci 2024;15(e41):e41; doi: 10.34172/jlms.2024.41

22.

22. Minaz

, Alam

, Jiwani

, et al. Efficacy of probiotics for treatment of acute or persistent diarrhoea in children from birth till 10 years: Systematic review and meta-analysis. J Glob Health 2024;14:e04236; doi: 10.7189/jogh.14.04236

23.

23. Fernandez

, Sharifnia

, Khalil

. Umbrella reviews: A methodological guide. Eur J Cardiovasc Nurs 2025;24(6):996–1002; doi: 10.1093/eurjcn/zvaf012

24.

24. Zarezadeh

, Musazadeh

, Ghalichi

, et al. Effects of probiotics supplementation on blood pressure: An umbrella meta-analysis of randomized controlled trials. Nutr Metab Cardiovasc Dis 2023;33(2):275–286; doi: 10.1016/j.numecd.2022.09.005

25.

25. Han

, Ren

, Zhang

, et al. The effectiveness of treatment with probiotics in preventing necrotizing enterocolitis and related mortality: Results from an umbrella meta-analysis on meta-analyses of randomized controlled trials. BMC Gastroenterol 2025;25(1):245; doi: 10.1186/s12876-025-03788-0

26.

26. DerSimonian

, Laird

. Meta-analysis in clinical trials revisited. Contemp Clin Trials 2015;45(Pt A):139–145; doi: 10.1016/j.cct.2015.09.002

27.

27. Ahmadi

, Alizadeh-Navaei

, Rezai

. Efficacy of probiotic use in acute rotavirus diarrhea in children: A systematic review and meta-analysis. Caspian J Intern Med 2015;6(4):187–195. PMCID: PMC4649266

28.

28. Allen

, Martinez

, Gregorio

, Dans

. Probiotics for treating acute infectious diarrhoea. Cochrane Database Syst Rev 2010;2010(11):CD003048; doi: 10.1002/14651858.CD003048.pub3

29.

29. Cheng

, Ma

, Liu

, et al. A systematic review and meta-analysis: Lactobacillus acidophilus for treating acute gastroenteritis in children. Nutrients 2022;14(3):682; doi: 10.3390/nu14030682

30.

30. Di

J-B

, Gai

Z-T

. Protective efficacy of probiotics on the treatment of acute rotavirus diarrhea in children: An updated meta-analysis. Eur Rev Med Pharmacol Sci 2020;24(18):9675–9683; doi: 10.26355/eurrev_202009_23057

31.

31. Dinleyici

, Eren

, Ozen

, et al. Effectiveness and safety of Saccharomyces boulardii for acute infectious diarrhea. Expert Opin Biol Ther 2012;12(4):395–410; doi: 10.1517/14712598.2012.664129

32.

32. Feizizadeh

, Salehi-Abargouei

, Akbari

. Efficacy and safety of Saccharomyces boulardii for acute diarrhea. Pediatrics 2014;134(1):e176–e191; doi: 10.1542/peds.2013-3950

33.

33. Florez

, Veroniki

A-A

, Al Khalifah

, et al. Comparative effectiveness and safety of interventions for acute diarrhea and gastroenteritis in children: A systematic review and network meta-analysis. PLoS One 2018;13(12):e0207701; doi: 10.1371/journal.pone.0207701

34.

34. Fu

, Li

, Xu

, et al. Effectiveness and safety of saccharomyces boulardii for the treatment of acute gastroenteritis in the pediatric population: A systematic review and meta‐analysis of randomized controlled trials. Comput Math Methods Med 2022;2022(1):6234858; doi: 10.1155/2022/6234858

35.

35. Higuchi

, Furuichi

, Maeda

, et al. Effects of probiotics in children with acute gastroenteritis: A systematic review and meta-analysis focusing on probiotics utilized in Japan. J Infect Chemother 2024;30(4):337–342; doi: 10.1016/j.jiac.2023.11.005

36.

36. Ianiro

, Rizzatti

, Plomer

, et al. Bacillus clausii for the treatment of acute diarrhea in children: A systematic review and meta-analysis of randomized controlled trials. Nutrients 2018;10(8):1074; doi: 10.3390/nu10081074

37.

37. Kambale

, Nancy

, Ngaboyeka

, et al. Effects of probiotics and synbiotics on diarrhea in undernourished children: Systematic review with meta-analysis. Clin Nutr 2021;40(5):3158–3169; doi: 10.1016/j.clnu.2020.12.026

38.

38. Li

Y-T

, Xu

, Ye

J-Z

, et al. Efficacy of Lactobacillus rhamnosus GG in treatment of acute pediatric diarrhea: A systematic review with meta-analysis. World J Gastroenterol 2019;25(33):4999–5016; doi: 10.3748/wjg.v25.i33.4999

39.

39. Malagón-Rojas

, Mantziari

, Salminen

, Szajewska

. Postbiotics for preventing and treating common infectious diseases in children: A systematic review. Nutrients 2020;12(2):389; doi: 10.3390/nu12020389

40.

40. McFarland

, Srinivasan

, Setty

, et al. Specific probiotics for the treatment of pediatric acute gastroenteritis in India: A systematic review and meta-analysis. JPGN Rep 2021;2(3):e079; doi: 10.1097/PG9.0000000000000079

41.

41. Salari

, Nikfar

, Abdollahi

. A meta-analysis and systematic review on the effect of probiotics in acute diarrhea. Inflamm Allergy Drug Targets 2012;11(1):3–14; doi: 10.2174/187152812798889394

42.

42. Sazawal

, Hiremath

, Dhingra

, et al. Efficacy of probiotics in prevention of acute diarrhoea: A meta-analysis of masked, randomised, placebo-controlled trials. Lancet Infect Dis 2006;6(6):374–382; doi: 10.1016/S1473-3099(06)70495-9

43.

43. Sun

, Kong

, Zhu

, Liu

. A systematic review and meta-analysis: The therapeutic and preventive effect of Lactobacillus reuteri DSM 17,938 addition in children with diarrhea. BMC Gastroenterol 2023;23(1):141; doi: 10.1186/s12876-023-02778-4

44.

44. Szajewska

, Kołodziej

, Gieruszczak‐Białek

, et al. Systematic review with meta‐analysis: Lactobacillus rhamnosus GG for treating acute gastroenteritis in children–a 2019 update. Aliment Pharmacol Ther 2019;49(11):1376–1384; doi: 10.1111/apt.15267

45.

45. Szajewska

, Kołodziej

, Zalewski

. Systematic review with meta‐analysis: Saccharomyces boulardii for treating acute gastroenteritis in children—a 2020 update. Aliment Pharmacol Ther 2020;51(7):678–688; doi: 10.1111/apt.15659

46.

46. Szajewska

, Mrukowicz

. Probiotics in the treatment and prevention of acute infectious diarrhea in infants and children: A systematic review of published randomized, double‐blind, placebo‐controlled trials. J Pediatr Gastroenterol Nutr 2001;33 Suppl 2(Suppl 2):S17–S25; doi: 10.1097/00005176-200110002-00004

47.

47. Szajewska

, Ruszczyński

, Kolaček

. Meta‐analysis shows limited evidence for using Lactobacillus acidophilus LB to treat acute gastroenteritis in children. Acta Paediatr 2014;103(3):249–255; doi: 10.1111/apa.12487

48.

48. Szajewska

, Skórka

. Saccharomyces boulardii for treating acute gastroenteritis in children: Updated meta‐analysis of randomized controlled trials. Aliment Pharmacol Ther 2009;30(9):960–961; doi: 10.1111/j.1365-2036.2009.04113.x

49.

49. Szajewska

, Skorka

, Dylag

. Meta‐analysis: Saccharomyces boulardii for treating acute diarrhoea in children. Aliment Pharmacol Ther 2007;25(3):257–264; doi: 10.1111/j.1365-2036.2006.03202.x

50.

50. Szajewska

, Skorka

, Ruszczyński

, Gieruszczak‐Białek

. Meta‐analysis: Lactobacillus GG for treating acute gastroenteritis in children–updated analysis of randomised controlled trials. Aliment Pharmacol Ther 2013;38(5):467–476; doi: 10.1111/apt.12403

51.

51. Szajewska

, Skórka

, Ruszczyński

, Gieruszczak‐Białek

. Meta‐analysis: Lactobacillus GG for treating acute diarrhoea in children. Aliment Pharmacol Ther 2007;25(8):871–881; doi: 10.1111/j.1365-2036.2007.03282.x

52.

52. Szajewska

, Urbańska

, Chmielewska

, et al. Meta-analysis: Lactobacillus reuteri strain DSM 17938 (and the original strain ATCC 55730) for treating acute gastroenteritis in children. Benef Microbes 2014;5(3):285–293; doi: 10.3920/BM2013.0056

53.

53. Urbańska

, Gieruszczak‐Białek

, Szajewska

. Systematic review with meta‐analysis: Lactobacillus reuteri DSM 17938 for diarrhoeal diseases in children. Aliment Pharmacol Ther 2016;43(10):1025–1034; doi: 10.1111/apt.13590

54.

54. Van Niel

, Feudtner

, Garrison

, Christakis

. Lactobacillus therapy for acute infectious diarrhea in children: A meta-analysis. Pediatrics 2002;109(4):678–684; doi: 10.1542/peds.109.4.678

55.

55. Vassilopoulou

, Spyromitrou-Xioufi

, Ladomenou

. Effectiveness of probiotics and synbiotics in reducing duration of acute infectious diarrhea in pediatric patients in developed countries: A systematic review and meta-analysis. Eur J Pediatr 2021;180(9):2907–2920; doi: 10.1007/s00431-021-04046-7

56.

56. Vecchio

, Nunziata

, Bruzzese

, et al. Rotavirus immunisation status affects the efficacy of Lacticaseibacillus rhamnosus GG for the treatment of children with acute diarrhoea: A meta-analysis. Benef Microbes 2022;13(4):283–294; doi: 10.3920/BM2022.0024

57.

57. Wu

, Zhan

. Systematic review with meta‐analysis: Probiotics for treating acute diarrhoea in children with dehydration. J Paediatr Child Health 2021;57(3):431–439; doi: 10.1111/jpc.15243

58.

58. Yang

, Lu

, Li

M-X

, et al. A meta-analysis of the effects of probiotics and synbiotics in children with acute diarrhea. Medicine (Baltimore) 2019;98(37):e16618; doi: 10.1097/MD.0000000000016618

59.

59. Chmielewska

, Ruszczynski

, Szajewska

. Lactobacillus reuteri strain ATCC 55730 for the treatment of acute infectious diarrhoea in children: A meta-analysis of randomized controlled trials. Pediatria Wspolczesna 2008;10(1):32.

60.

60. Alsabri

, Rath

, Abo‐elnour

, et al. Efficacy of probiotics in reducing the duration and severity of acute gastroenteritis in children: A meta‐analysis of randomized controlled trials. J Pediatr Gastroenterol Nutr 2025;81(4):1000–1009; doi: 10.1002/jpn3.70172

61.

61. McFarland

, Li

. Efficacy and safety of Saccharomyces boulardii CNCM I-745 for the treatment of pediatric acute diarrhea in China: A systematic review and meta-analysis. Front Cell Infect Microbiol 2025;15:1587792; doi: 10.3389/fcimb.2025.1587792

62.

62. Michel

, Pellegrino

. A comprehensive review and meta-analysis on the treatment of acute gastroenteritis in children with a Bacillus clausii preparation (Enterogermina^®). Adv Ther 2025;42(7):3076–3088; doi: 10.1007/s12325-025-03221-8

63.

63. Corbett

, Higgins

, Woolacott

. Assessing baseline imbalance in randomised trials: Implications for the Cochrane risk of bias tool. Res Synth Methods 2014;5(1):79–85; doi: 10.1002/jrsm.1090

64.

64. Mohsina

, Gurushankari

, Niranjan

, et al. Assessment of the quality of randomized controlled trials in surgery using Jadad score: Where do we stand? J Postgrad Med 2022;68(4):207–212; doi: 10.4103/jpgm.JPGM_104_21

65.

65. Hudson

, McDermott

, Stewart

, et al. Characterization of the probiotic yeast Saccharomyces boulardii in the healthy mucosal immune system. PLoS One 2016;11(4):e0153351; doi: 10.1371/journal.pone.0153351

66.

66. Stier

, Bischoff

. Influence of Saccharomyces boulardii CNCM I-745on the gut-associated immune system. Clin Exp Gastroenterol 2016;9:269–279; doi: 10.2147/CEG.S111003

67.

67. Van den Abbeele

, Duysburgh

, Rakebrandt

, Marzorati

. Dried yeast cell walls high in beta-glucan and mannan-oligosaccharides positively affect microbial composition and activity in the canine gastrointestinal tract in vitro. J Anim Sci 2020;98(6):skaa173; doi: 10.1093/jas/skaa173

68.

68. Pais

, Almeida

, Yılmaz

, Teixeira

. Saccharomyces boulardii: What makes it tick as successful probiotic? J Fungi (Basel) 2020;6(2):78; doi: 10.3390/jof6020078

69.

69. Derrien

, van Hylckama Vlieg

. Fate, activity, and impact of ingested bacteria within the human gut microbiota. Trends Microbiol 2015;23(6):354–366; doi: 10.1016/j.tim.2015.03.002

70.

70. Lebeer

, Vanderleyden

, De Keersmaecker

. Host interactions of probiotic bacterial surface molecules: Comparison with commensals and pathogens. Nat Rev Microbiol 2010;8(3):171–184; doi: 10.1038/nrmicro2297

71.

71. Mishima

, Oka

, Liu

, et al. Microbiota maintain colonic homeostasis by activating TLR2/MyD88/PI3K signaling in IL-10–producing regulatory B cells. J Clin Invest 2019;129(9):3702–3716; doi: 10.1172/JCI93820

72.

72. Allen

, Martinez

, Gregorio

, Dans

. Probiotics for treating acute infectious diarrhoea. Sao Paulo Med J 2011;129(3):185; doi: 10.1590/S1516-31802011000300012

73.

73. Dang

, Phung

TTB

, Tran

, et al. High-dose multi-strain Bacillus probiotics enhance treatment and reduce antibiotic usage in children with persistent diarrhea through immune and microbiota modulation. Sci Rep 2025;15(1):30231; doi: 10.1038/s41598-025-15199-y

74.

74. Ojetti

, Petruzziello

, Migneco

, et al. Impact of oral administration of Lactobacillus reuteri LMG-P 27481 on human gut microbiota diversity and function: A pilot study. Biomedicines 2025;13(11):2840; doi: 10.3390/biomedicines13112840

75.

75. Poncelet

, Ruelle

, Konopnicki

, et al. Saccharomyces cerevisiae fungemia: Risk factors, outcome and links with S. Boulardii-containing probiotic administration. Infect Dis Now 2021;51(3):293–295; doi: 10.1016/j.idnow.2020.12.003

76.

76. Lherm

, Monet

, Nougière

, et al. Seven cases of fungemia with Saccharomyces boulardii in critically ill patients. Intensive Care Med 2002;28(6):797–801; doi: 10.1007/s00134-002-1267-9

77.

77. do Carmo

, Santos

CID

, Araújo

, et al. Probiotics, mechanisms of action, and clinical perspectives for diarrhea management in children. Food Funct 2018;9(10):5074–5095; doi: 10.1039/c8fo00376a

78.

78. Van Zyl

, Deane

, Dicks

. Molecular insights into probiotic mechanisms of action employed against intestinal pathogenic bacteria. Gut Microbes 2020;12(1):1831339; doi: 10.1080/19490976.2020.1831339

79.

79. Corr

, Hill

, Gahan

. Understanding the mechanisms by which probiotics inhibit gastrointestinal pathogens. Adv Food Nutr Res 2009;56:1–15; doi: 10.1016/S1043-4526(08)00601-3

80.

80. Yousefi

, Eslami

, Ghasemian

, et al. Probiotics importance and their immunomodulatory properties. J Cell Physiol 2019;234(6):8008–8018; doi: 10.1002/jcp.27559

81.

81. Abbas

, Yakoob

, Jafri

, et al. Cytokine and clinical response to Saccharomyces boulardii therapy in diarrhea-dominant irritable bowel syndrome: A randomized trial. Eur J Gastroenterol Hepatol 2014;26(6):630–639; doi: 10.1097/MEG.0000000000000094

82.

82. Gedek

. Adherence of Escherichia coli serogroup 0 157 and the Salmonella typhimurium mutant DT 104 to the surface of Saccharomyces boulardii. Mycoses 1999;42(4):261–264; doi: 10.1046/j.1439-0507.1999.00449.x

83.

83. Fusco

, Savio

, Cammarota

, et al. Beta‐defensin‐2 and beta‐defensin‐3 reduce intestinal damage caused by salmonella typhimurium modulating the expression of cytokines and enhancing the probiotic activity of Enterococcus faecium. J Immunol Res 2017;2017(1):6976935; doi: 10.1155/2017/6976935

84.

84. María Remes-Troche

, Coss-Adame

, Ángel Valdovinos-Díaz

, et al. Lactobacillus acidophilus LB: A useful pharmabiotic for the treatment of digestive disorders. Therap Adv Gastroenterol 2020;13; doi: 10.1177/1756284820971201

85.

85. Gao

, Li

, Wan

, et al. A novel postbiotic from Lactobacillus rhamnosus GG with a beneficial effect on intestinal barrier function. Front Microbiol 2019;10:477; doi: 10.3389/fmicb.2019.00477

86.

86. Wang

, Liu

, Kirpich

, et al. Lactobacillus rhamnosus GG reduces hepatic TNFα production and inflammation in chronic alcohol-induced liver injury. J Nutr Biochem 2013;24(9):1609–1615; doi: 10.1016/j.jnutbio.2013.02.001

87.

87. Alves

, Lemos

, Rodrigues

, et al. Immunomodulatory effects of different strains of Lactococcus lactis in DSS-induced colitis. Braz J Microbiol 2023;54(2):1203–1215; doi: 10.1007/s42770-023-00928-0

88.

88. Liu

, Fatheree

, Mangalat

, Rhoads

. Lactobacillus reuteri strains reduce incidence and severity of experimental necrotizing enterocolitis via modulation of TLR4 and NF-κB signaling in the intestine. Am J Physiol Gastrointest Liver Physiol 2012;302(6):G608–G617; doi: 10.1152/ajpgi.00266.2011

89.

89. Graul

, Cain

, Karpa

. Lactobacillus and bifidobacteria combinations: A strategy to reduce hospital-acquired Clostridium difficile diarrhea incidence and mortality. Med Hypotheses 2009;73(2):194–198; doi: 10.1016/j.mehy.2009.02.026

90.

90. Lopetuso

, Scaldaferri

, Franceschi

, Gasbarrini

. Bacillus clausii and gut homeostasis: State of the art and future perspectives. Expert Rev Gastroenterol Hepatol 2016;10(8):943–948; doi: 10.1080/17474124.2016.1200465

91.

91. Rehman

, Nisar

, Mercado

, et al. BACILLUS CLAUSII: A PROBIOTIC APPROACH TO COMBATING INTESTINAL INFECTIONS. J Med Health Sci Rev 2025;2(2); doi: org/10.62019/7pd46t17

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.02 MB

6.52 MB

0.03 MB

0.06 MB

0.00 MB