Effects of the Use of Probiotics in Post-Bariatric Surgery Obesity: Meta-Umbrella of Systematic Reviews

Abstract

Obesity is a multifaceted health issue linked to conditions like type 2 diabetes, hypertension, and cardiovascular disease. Bariatric surgery is a well-established method for significant weight loss and health improvement, but maintaining weight loss and recovering post-surgery can be challenging. Probiotics, beneficial live microorganisms, are suggested as potential aids in managing obesity and its complications, but research on their effectiveness in this context is limited and diverse. This study aimed to evaluate the impact of probiotics on obesity in individuals post-bariatric surgery. A meta-umbrella review was conducted, analyzing systematic reviews and meta-analyses of probiotics’ effects. The review included studies from PubMed, Scopus, EMBASE, and Cochrane Library, focusing on weight loss, body composition, and metabolic parameters. Four systematic reviews met the criteria. The findings indicate that probiotics may significantly reduce waist circumference and body weight, and improve lipid and liver markers. However, their effects on glycemic parameters, quality of life, and adverse events were less clear. Overall, probiotics might offer modest benefits in managing weight and improving certain metabolic parameters after bariatric surgery. However, their overall efficacy, especially regarding glycemic control and quality of life, remains uncertain. Further high-quality research is needed to confirm these findings and elucidate the mechanisms involved.

1. Introduction

Obesity is a multifaceted health condition characterized by excessive fat accumulation, significantly increasing the risk of physical and mental health issues, including type 2 diabetes, hypertension, and cardiovascular disease [1]. The prevalence of obesity has steadily risen over the past few decades, making it a pressing public health issue with profound implications for individuals and healthcare systems. Its complexity stems from an interplay of genetic, environmental, and behavioral factors contributing to its development and persistence [2].

Bariatric surgery has emerged as a highly effective intervention for individuals with severe obesity, leading to substantial weight loss and improvements in obesity-related health conditions. Procedures such as Roux-en-Y gastric bypass, sleeve gastrectomy, and adjustable gastric banding have demonstrated significant efficacy in reducing body mass index (BMI) and ameliorating metabolic abnormalities [3]. However, despite these successes, the post-surgical period presents its own set of challenges. Patients often face difficulties in maintaining weight loss, managing post-operative complications, and achieving long-term health improvements [4].

One of the critical aspects of post-bariatric surgery management is optimizing recovery and maintaining weight loss over the long term. While lifestyle modifications, including diet and exercise, are central to achieving these goals, additional supportive interventions may be necessary to enhance outcomes [5]. Probiotics, defined as live microorganisms that confer health benefits when administered in adequate amounts, have been proposed as potential adjuncts in managing obesity. These beneficial bacteria can influence gut microbiota composition, increasingly recognized for its role in metabolic regulation and weight management [6].

The concept of using probiotics to support post-bariatric surgery patients is rooted in their potential to impact several physiological processes. Probiotics may improve gut health, enhance nutrient absorption, and modulate inflammatory responses, which can benefit individuals recovering from bariatric surgery [7]. Furthermore, evidence suggests that probiotics could influence appetite regulation and energy metabolism, which are critical factors in weight management and obesity treatment [8].

However, the use of probiotics in this context remains underexplored, particularly given the heterogeneous nature of post-bariatric surgery patients. Factors such as the type of surgical procedure, individual variations in gut microbiota, and differing probiotic strains could all impact the effectiveness of these supplements. This variability underscores the need for a comprehensive evaluation of how probiotics might benefit post-bariatric surgery patients and whether they can reliably contribute to sustained weight loss and improved metabolic health [9].

Despite the theoretical benefits, the current body of research on probiotics in the context of bariatric surgery presents mixed findings. Some studies have reported positive effects on weight management and metabolic parameters, while others have found limited or no significant impact. This inconsistency highlights the importance of synthesizing existing evidence to provide clearer insights into the role of probiotics for this patient population [1].

A meta-umbrella review of systematic reviews is well-suited to address this gap by aggregating and analyzing data from multiple systematic reviews that have investigated the effects of probiotics in post-bariatric surgery patients. Such a review will help clarify the overall efficacy, safety, and potential benefits of probiotic supplementation in this specific context.

By examining the evidence from various systematic reviews, this umbrella review aims to provide a comprehensive assessment of the impact of probiotics on obesity following bariatric surgery. The focus will be on understanding how probiotics influence weight management, metabolic health, and overall recovery in post-surgical patients. This review seeks to identify any patterns, strengths, and limitations in the existing research to offer practical recommendations for integrating probiotics into post-bariatric surgery care.

The ultimate objective of this review is to evaluate the effects of probiotic supplementation on obesity in individuals who have undergone bariatric surgery. Through a rigorous analysis of existing systematic reviews, the review will provide valuable insights into whether probiotics can be considered a viable adjunct to standard post-surgical care and contribute to improved long-term outcomes for these patients.

2. Materials and Methods

The umbrella was conducted in accordance with the JBI methodology and the Reporting Guideline for Overviews of Health Interventions [10]. To ensure comprehensive reporting, the review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) [11] guidelines and was prospectively registered in PROSPERO (CRD42024584190).

The search began in the second half of 2024, in the databases specified below. No language or date restrictions were applied.

The following sources were researched:

• Web of Science
• PubMed
• Scope
• BASE
• Cochrane
• Epistemonikos
• CINAHL

A preliminary search was carried out in PROSPERO to identify a possible review in progress, and none was identified.

Based on the established research question, we developed a preliminary search strategy for Medline/Pubmed using the ECUs (Extraction, Conversion, Combination, and Use) method steps. To ensure the feasibility of the method, we followed the guidelines of the Peer Review of Electronic Search Strategies (PRESS) checklist [12].

Research question:

How effective are probiotics in improving metabolic outcomes in obese patients after bariatric surgery?

PICO(S) structure:

• P (Population): Post-bariatric surgery patients with obesity.
• I (Intervention): Use of probiotics (food supplements).
• C (Comparison): Other forms of standard treatment (usual care, conventional treatment).
• O (Outcome): Metabolic effects.
• S (Study): Systematic reviews and meta-analyses.

Extracted Descriptors:

• Category:

  ○

  P: Post-bariatric surgery patients with obesity.

  ○

  I: Probiotics, dietary supplements.

  ○

  C: Standard care, usual care, conventional treatment.

  ○

  O: Metabolic effects.

  ○

  S: Systematic reviews, meta-analyses.

Search Term Combination:

• P (Population): (“post-bariatric surgery” OR “bariatric surgery patients” OR “post-surgery obesity”) AND (“obesity” OR “obese patients”)
• I (Intervention): (“probiotics” OR “probiotic supplements” OR “probiotic therapy” OR “probiotic treatment”)
• C (Comparison): (“standard care” OR “usual care” OR “conventional treatment” OR “traditional care” OR “routine care” OR “standard medical care” OR “standard clinical care”)
• O (Outcome): (“metabolic effects” OR “metabolic results” OR “metabolic health”)
• S (Study): (review OR “systematic review” OR “systematic literature review” OR “meta-analysis” OR “meta-analysis” OR overview OR “rapid review” OR “integrative review” OR “scoping review”)

The inclusion and exclusion criteria considered were as follows:

Inclusion Criteria:

• Studies focusing on post-bariatric surgery patients with obesity.
• Interventions involving the use of probiotics as dietary supplements.
• Comparisons with other forms of standard care or conventional treatments.
• Studies reporting metabolic outcomes.
• Only systematic reviews and meta-analyses were included.

Exclusion Criteria:

• Studies that do not provide separate data for post-bariatric surgery patients.
• Studies involving interventions other than probiotics or focusing on non-metabolic outcomes.
• Studies without adequate methodological rigor.
• Studies that do not fall under the scope of systematic reviews and meta-analyses.

Search Strategy Construction:

To ensure a comprehensive approach, the search strategy included terms related to the health context of post-bariatric surgery patients with obesity. The final search was:

(“post-bariatric surgery” OR “bariatric surgery patients” OR “post-surgery obesity”) AND (“obesity” OR “obese patients”) AND (“probiotics” OR “probiotic supplements” OR “probiotic therapy” OR “probiotic treatment”) AND (review OR “systematic review” OR “systematic literature review” OR “meta-analysis” OR “meta-analysis” OR overview OR “rapid review” OR “integrative review” OR “scoping review”).

Four controlled vocabularies were used to develop the search strategy: Medical Subject Headings (MeSH), Embase’s EMTREE, CINAHL Subject Headings, and Health Sciences Descriptors (DeCS). These controlled terms were combined with natural language free text terms, along with the Boolean operators AND and OR, to increase search sensitivity and obtain a broader spectrum of relevant results.

A variation in Portuguese was made for the LILACS bibliographic database. In the Scopus and Web of Science databases, which do not have an integrated controlled vocabulary, we used the standard search strategy. In the other bibliographic databases, we used the standard search strategy together with their respective specific subject headings.

Searches of all databases were conducted on the same day to avoid potential bias. Initially, a preliminary search was conducted on 30 July 2024, in the MEDLINE (Medical Literature Analysis and Retrieval System Online) database via PubMed, and it was subsequently adjusted in other electronic databases.

The bibliographic search was complemented by checking the reference lists of the included documents and with suggestions from experts in post-bariatric surgery obesity.

After the research was completed, all identified citations were compiled and entered into the Mendeley citation management system, with systematic removal of duplicates.

Subsequently, the records were imported into the Rayyan QCRI reference manager [13]. This tool allows fast and accurate processes, as it allows the removal of duplicate studies and selection and screening of studies. In addition, it maintains methodological rigor and transparency among examiners, as it allows blind evaluation (Blind ON), thus avoiding possible biases [13].

The study screening and selection process was performed by two reviewers independently, and the data were double-checked by the authors. Study management consisted of three phases. The first phase involved reading the titles and abstracts to identify potentially relevant studies. In the second phase, the full texts of the selected studies were reviewed to confirm their eligibility according to the inclusion and exclusion criteria. The third and final phase involved manually searching the reference lists of the included studies to identify any additional relevant publications that may not have been captured during the initial database search. The first phase involved reading the titles and abstracts.

To verify the agreement between the evaluators in the other selection phases, Cohen’s kappa coefficient [14] was calculated, presenting the following classification: 0–0.20, none; 0.21–0.39, minimal; 0.40–0.59, weak; 0.60–0.79, moderate; 0.80–0.90 strong; above 90, almost perfect. If there is agreement less than or equal to 0.79, training was carried out among the evaluators to increase the reliability of the process. For this, 30 studies were chosen to carry out the test with the evaluators.

Studies that met the inclusion criteria proceeded to the second phase. This involved reading the studies in full and selecting the studies that would be included in the review. Finally, the third stage involved manual searches of the references of the included studies. The entire identification, screening, and inclusion process was documented in the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) flowchart.

Two independent reviewers extracted data using a previously defined extraction form. If any information in the included reviews was unclear or missing, the review authors were contacted for clarification. Extraction was carried out considering the following data:

• Review references: Basic information about each systematic review (authors, year of publication, title, source, etc.).
• Number of studies included: Number of primary studies included in each review.
• Population studied: Demographic characteristics of participants in the included reviews, such as mean age, sex, and specific health conditions, with a focus on the population who underwent bariatric surgery and developed post-operative obesity.

Intervention data:

• Type of probiotic: Details about the probiotics used, including specific strains, dose, frequency, and duration of treatment.
• Method of Administration: Description of how the probiotics were administered (oral, capsules, liquids, etc.).

Data on comparators:

• Type of comparator: Description of the control groups or comparators, such as placebo or standard treatments, used in the reviews.
• Comparator characteristics: Details about the standard treatments or controls used for comparison with the probiotic intervention.

Data on metabolic outcomes and obesity:

• Metabolic measurements: Metabolic indicators evaluated, such as blood glucose, HbA1c, lipid profile, and blood pressure, among others relevant to obesity after bariatric surgery.
• Metabolic outcomes: Effects of probiotics on metabolic parameters such as glycemic control, lipid profile, and other indicators of metabolic health after bariatric surgery.
• Obesity measures: Specific indicators of obesity, such as body mass index (BMI), abdominal circumference, body fat percentage, etc.
• Results on obesity: Effects of probiotics on obesity, such as changes in BMI and reduction in body fat, among other specific indicators of obesity after bariatric surgery.

This extraction format ensured a detailed analysis of the effects of probiotics in individuals with obesity after bariatric surgery, with an exclusive focus on outcomes related to obesity and metabolic health.

For reviews without meta-analysis, a summary of the authors’ primary interpretation of the results was extracted. For meta-analyses, data on pooled effect sizes (e.g., rate ratios, risk ratios, odds ratios for dichotomous data, and mean difference or standardized mean difference for continuous data) as well as corresponding 95% CIs and p values were extracted.

Systematic reviews exploring similar topics may have considerable overlap with the primary studies included. We created a citation matrix and calculated the corrected coverage area (CCA) index to analyze the overlap in the primary studies included in the reviews [15]. Based on guidance from Hennessy and Johnson (2020) [16], we further examined the reasons for overlap based on the CCA score. Reviews with complete/near complete overlap were examined for reasons of high overlap and considered for exclusion; higher quality (e.g., Cochrane reviews) and/or more recent reviews (if ratings were similar) were retained.

Study selection and assessment were conducted by two reviewers using the JBI Critical Appraisal Checklist for Systematic Reviews and Research Synthesis. The tool consists of 11 items that assess the following: (i) clarity of the review question; (ii) adequacy of inclusion criteria; (iii) adequacy of the search strategy; (iv) adequacy of sources and resources used to search for studies; (v) adequacy of assessment criteria; (vi) assessment of duplicate quality; (vii) applications used to minimize errors in data extraction; (viii) adequacy of methods used to combine studies; (ix) assessment of publication bias; (x) robustness of recommendations for policy and practice; and (xi) adequacy of proposed new research directions. Items are scored based on the checklist as “Y = fulfilled”, “N = not fulfilled”, “? = unclear”, and “NA = not applicable”.

The data were double-checked by the authors. If additional information was needed, the study authors were contacted.

The decision to include studies was based on a predefined score of 7 or higher. The reference criteria for the scores are as follows: a score of 0–3 was classified as very low quality, 4–6 as low quality, 7–9 as moderate quality, and a score of 10–11 was considered high quality. The A MeaSurement Tool to Assess systematic Reviews (AMSTAR) checklist [17] was also used.

The results of the critical appraisal were reported in a table accompanied by a narrative. All studies underwent data extraction and synthesis; however, depending on the overall results of the critical appraisal, sensitivity analyses were performed to test the robustness of our conclusions.

The evaluation was conducted using the JBI Critical Appraisal Checklist for Systematic Reviews and Research Synthesis. This tool assessed various aspects, such as the clarity of the review question, the adequacy of the search strategy, and the methods used to minimize errors. In addition, the AMSTAR tool was used to complement the evaluation, ensuring a comprehensive analysis of the risk of bias. This information was incorporated into the relevant section of the manuscript.

The included reviews were descriptively synthesized and then, if possible, the data were meta-analyzed.

Heterogeneity between studies is rigorously assessed using statistics such as the I² index. The methodological quality and publication bias of systematic reviews were considered in the interpretation of the results. The combined results were presented in a clear and transparent manner, highlighting the limitations and robustness of the conclusions. A meta-umbrella not only contributes to effective synthesis of evidence, but also points to knowledge gaps and guides future research in the area. The analyses involved the calculation of odds ratios and linear correlation, according to the retrieved data.

The REML model was used as an estimator between studies and a multivariate analysis between outcomes was performed. It is a statistical method used to estimate parameters in variance–covariance models, especially in mixed linear models [18]. For stratification of the evidence, the number of studies, total number of participants, number of cases, p-value of outcomes, inconsistency, imprecision, risk of bias, and quality of meta-analysis, predictions, and outcomes of each research were considered. The “metaumbrella” package was used applying some specific tests for analysis, fixed effect or random effects meta-analysis, inconsistency/heterogeneity assessment (I²), tests for small study effects, and tests of excess statistical significance. The result of the inferential analysis was demonstrated using the forest plot. The R 4.3.2 software was used.

When summarizing the findings of the reviews, we used the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) principles ¹¹ for an overall assessment of the quality of evidence in the reviews for outcomes of interest. The quality of evidence for a given outcome was graded as high, moderate, or low based on the overall quality of the systematic reviews and the risk of bias in the primary studies, as well as the consistency of the results.

3. Results

Out of the 72 studies initially identified, 4 systematic reviews met the inclusion criteria for this meta-umbrella review (

Table 1. Information extracted from the studies.

Author (Year)	Objective	Guideline Used	Results	Conclusions	Probiotic Type	Intervention Period	AMSTAR Score
Wang et al. (2023) [19]	To assess the effects of probiotics in patients with obesity undergoing bariatric surgery.	PRISMA, GRADE, AMSTAR 2 Checklist	Probiotics significantly reduced AST, triglycerides, weight, and food intake. No severe side effects reported.	Probiotics may delay liver function injury progression, improve lipid metabolism, reduce weight, and decrease food intake in bariatric patients.	Primarily Lactobacillus and Bifidobacterium strains; some studies used Bacillus species.	3 months to 6 months	10/16
Świerz et al. (2020) [9]	To assess the efficacy and safety of probiotics in patients with obesity undergoing bariatric surgery.	PRISMA, Cochrane RoB, GRADE, AMSTAR 2 Checklist	Probiotics may have minor to no effect on %EWL at different follow-up periods. Short-term improvement in gastrointestinal symptoms observed.	Probiotic supplementation might provide some benefit for weight loss and gastrointestinal symptoms but with very low certainty of evidence.	Various species including Lactobacillus casei, Lactobacillus rhamnosus, Streptococcus thermophilus, Bifidobacterium breve, Lactobacillus acidophilus, Bifidobacterium longum, and others depending on the study.	6 weeks to 12 months	9/16
Cook et al. (2020) [20]	To evaluate the interaction between gut microbiota, probiotics, and psychological states and behaviors in patients after bariatric surgery.	PRISMA, PROSPERO	Probiotics were not superior to placebo in improving quality of life or weight loss post-bariatric surgery.	Probiotic supplementation did not significantly enhance post-operative outcomes in terms of quality of life or weight management. Further research needed to explore the gut–brain axis.	Single and multi-strain probiotics: Bifidobacterium longum, Lactobacillus, Bacillus coagulans, and a multi-strain mix (Bio-25).	14 days to 6 months	8/16
Zhang et al. (2021) [21]	To evaluate the effects of probiotics on body weight, BMI, %EWL, waist circumference (WC), and CRP in adults with obesity after bariatric surgery.	PRISMA, Cochrane RoB	Probiotics significantly reduced waist circumference at 12 months post-surgery, but no significant effect on weight, BMI, %EWL, or CRP.	Probiotics aid in reducing waist circumference after bariatric surgery but have no significant impact on weight, BMI, or other metabolic parameters.	Synbiotics (Lactobacillus paracasei, Lactobacillus rhamnosus, Lactobacillus acidophilus, Bifidobacterium lactis); also included a combination of 7 species of probiotics in other studies.	3 months to 12 months	10/16

). These selected reviews collectively evaluated the impact of probiotic supplementation in patients who had undergone bariatric surgery, revealing several notable findings regarding its efficacy on weight loss and metabolic health.

The systematic review and meta-analysis conducted by Yu Zhang et al. (2021) [21] focused on evaluating the effects of probiotics on various health outcomes in adults with obesity after bariatric surgery. The study found that while probiotics did not significantly impact weight, BMI, percentage of excess weight loss (%EWL), or C-reactive protein (CRP) within the first 12 months post-surgery, they did lead to a significant reduction in waist circumference at the 12-month follow-up. This suggests that probiotics may have a role in enhancing certain aspects of weight management, particularly in reducing abdominal fat, which is reflected in waist circumference rather than overall body weight.

However, the study also highlights that more high-quality clinical trials are needed to confirm the efficacy and safety of probiotics in this context. The results indicate that while probiotics can aid in the reduction of waist circumference, their overall impact on other metabolic parameters and weight loss remains limited. The authors recommend further research to explore the potential benefits of probiotics as an adjunct therapy for morbidly obese patients undergoing bariatric surgery.

The systematic review by Jessica Cook et al. (2020) [20] examined 59 studies to investigate the effects of bariatric surgery on gut microbiota, the role of probiotics, and their influence on psychological states and behaviors. The review included 30 studies on humans, 25 on other vertebrates, and 4 that specifically addressed probiotics in humans. The findings revealed that bariatric surgery generally leads to significant changes in the gut microbiota, including increased abundance of the phylum Proteobacteria and the genus Akkermansia, particularly the species Akkermansia muciniphila, which increased in six studies. However, these microbiota changes did not consistently correlate with improvements in psychological states or weight management outcomes.

In terms of probiotics, the review found that the effects on clinical outcomes such as body weight loss were minimal. For instance, in studies where probiotics were administered (ranging from 2.4 billion to over 25 billion bacteria per capsule for durations between 14 days and 6 months), the probiotics did not show a significant advantage over placebos in improving quality of life (QoL) or achieving greater weight loss. Increases in alpha diversity and shifts in the Firmicutes/Bacteroidetes ratio were observed, but these changes were also present in the control groups, indicating that probiotics did not offer substantial additional benefits post-surgery. The review concluded that while gut microbiota changes post-surgery are evident, the role of probiotics in enhancing psychological outcomes and weight loss remains inconclusive, necessitating further research.

The systematic review and meta-analysis by Yuting Wang et al. (2023) [19] focused on the effects of probiotics in patients with obesity undergoing bariatric surgery. The study included 11 randomized controlled trials (RCTs) with a total of 559 participants. The results indicated that probiotics had a significant impact on reducing aspartate aminotransferase (AST) levels by 4.32 U/L, triglycerides by 20.16 mg/dL, body weight by 1.99 kg, and daily caloric intake by 151.03 kcal. Additionally, probiotics were associated with improved vitamin B12 levels (an increase of 2.24 pg/dL). Despite these positive outcomes, probiotics did not show significant effects on glycemic parameters such as blood glucose, insulin, or HbA1c, and they did not significantly alter C-reactive protein (CRP) levels or other inflammatory markers.

The review also highlighted the lack of severe side effects associated with probiotic use, making them a potentially safe adjunct therapy for patients post-bariatric surgery. The authors concluded that while probiotics might help in managing liver function, lipid metabolism, weight, and certain nutritional parameters like vitamin B12, the overall effects on other critical health indicators remain uncertain. The study calls for more high-quality RCTs to further investigate the long-term benefits and precise mechanisms through which probiotics may aid patients with obesity who undergo bariatric surgery.

The systematic review and meta-analysis by Mateusz J. Świerz et al. (2020) [9] evaluated the efficacy of probiotics in patients with obesity undergoing bariatric surgery. The study included five randomized controlled trials with a total of 226 participants. The results indicated that probiotic supplementation had minor to no significant effect on percentage excess weight loss (%EWL) at different follow-up periods, including 6 weeks, 3 months, 6 months, and 12 months post-surgery. Specifically, the mean differences in %EWL between the probiotic and control groups were not significant across these time points, with very low certainty of evidence due to high risk of bias, imprecision, and inconsistency among the studies.

Additionally, while probiotics were associated with a short-term improvement in gastrointestinal symptoms, there was no meaningful impact on the quality of life or adverse events reported. The review suggests that, although probiotics might provide some benefit in alleviating gastrointestinal discomfort and are associated with minimal adverse effects, their role in enhancing long-term weight loss post-bariatric surgery is questionable. The authors concluded that continuous supplementation of probiotics could be considered for certain individuals, but the current evidence is insufficient to recommend routine use of probiotics post-surgery. Further well-designed trials are needed to clarify the effects of probiotics in this patient population.

The analysis of the overlap between the primary studies included in these four systematic reviews resulted in a corrected covered area (CCA) of approximately 0.393. This value indicates a moderate overlap among the reviews, suggesting that while there is some commonality in the primary studies included, the reviews also contain unique studies. A CCA value below 0.5 typically suggests that the reviews are relatively independent, with each contributing distinct information to the body of evidence. Therefore, there is no immediate need to exclude any of the reviews based on overlap alone.

However, the moderate overlap suggests that it would be prudent to consider other factors, such as the quality of the reviews (e.g., using AMSTAR scores) or the recency of their publication, when deciding which reviews to prioritize. The citation matrix heatmap illustrates the distribution of primary studies across the systematic reviews, visually confirming the moderate overlap. The reviews share some studies, but each also includes unique contributions, reinforcing the CCA’s indication of moderate overlap (Figure 1).

The forest plot by factors provides a visual summary of the overall effect sizes for different outcomes analyzed in the systematic reviews. Each horizontal line in the plot represents a specific factor, such as “% Excess Weight Loss”, “BMI”, or “CRP”. The dot in the middle of each line indicates the overall effect size for that factor, which is the weighted average of the effect sizes from all studies contributing to that factor. The horizontal lines extending from each dot represent the 95% confidence interval (CI) for the effect size. If a confidence interval crosses the vertical line at zero, it suggests that the effect might not be significant, meaning the true effect size could be zero or even in the opposite direction (Figure 2).

Interpreting the factors in the plot, we see that “% Excess Weight Loss” shows a positive effect with a confidence interval entirely above zero, indicating a significant improvement in excess weight loss. Similarly, CRP (C-reactive protein) displays a significant negative effect, meaning a reduction in CRP levels, which is typically associated with reduced inflammation. Factors like BMI and waist circumference also show negative effects, suggesting reductions in these metrics, but the wider confidence intervals, especially for BMI, indicate more uncertainty in the results. AST levels show a significant reduction, which is favorable for liver function, and weight loss is indicated by a negative overall effect size, with a narrow confidence interval suggesting consistency across studies.

On the other hand, some factors show non-significant effects. For example, the confidence interval for quality of life crosses zero, indicating that the intervention might not have had a significant impact on this outcome. Adverse events also have a confidence interval suggesting a potential increase, but this effect is not significant. Gastrointestinal symptoms show a slight improvement, but the result is not conclusive as the confidence interval includes zero. For vitamin B12 and triglycerides, the confidence intervals suggest potential benefits, such as improved B12 levels and reduced triglycerides, but the wide intervals indicate variability and uncertainty in these effects.

Overall, the forest plot highlights which factors show the most robust and consistent results across the included studies. Factors like CRP, AST levels, and waist circumference indicate consistent and significant effects, while those with wider confidence intervals or intervals crossing zero suggest that the evidence is less clear, possibly due to variability in the studies or insufficient data. This plot is valuable for identifying where the evidence is strongest and where further research might be needed, providing a clear comparison of the effects across different outcomes.

The forest plot presented offers a visual summary of the overall effect sizes for various factors evaluated in the meta-analysis. The meta-analysis was conducted using a random-effects model to account for variability between studies. The Q-statistic calculated was 47.08, indicating the presence of heterogeneity among the effect sizes. The I² value was 72.6%, suggesting that a substantial proportion of the variability is due to heterogeneity rather than chance. The τ² value, representing the variance of the true effect sizes in the random-effects model, was 4.29. The overall effect size, calculated as the weighted mean effect size, was close to 10, reflecting a positive direction. These statistical measures provide a clearer understanding of the variability among the studies and support the robustness of the overall findings. Each horizontal line represents a different factor, with the dot in the middle indicating the effect size and the lines extending from it showing the 95% confidence intervals (CI). The “Overall Effect − Combined Effect” at the top of the plot represents the aggregated effect size across all factors, and its confidence interval. The position of this dot to the left of zero suggests a general trend toward a negative effect, indicating that the interventions generally lead to reductions in the measured outcomes, such as weight, waist circumference, and CRP levels (Figure 3)).

The factors associated with significant negative effects include CRP, AST levels, and triglycerides, as indicated by their confidence intervals that do not cross the zero line. These factors suggest that the interventions studied, likely including probiotics or other treatments, had a strong impact in reducing these biomarkers, which are often associated with inflammation and metabolic health. The CRP factor, for example, shows a substantial reduction with a narrow confidence interval, indicating a consistent effect across studies. Similarly, waist circumference and excess weight loss are positively impacted, with confidence intervals entirely above zero, suggesting that the interventions were effective in promoting weight loss and reducing abdominal fat.

On the other hand, some factors, such as adverse events, quality of life, and gastrointestinal symptoms, show confidence intervals that cross the zero line, indicating that the results are not significant. This suggests variability in the effects of the interventions on these outcomes, with the possibility that the interventions may not have a consistent impact on these factors. The wide confidence intervals for these factors, especially for %EWL and triglycerides, indicate greater uncertainty in the results, reflecting either variability among the included studies or a lack of sufficient data to draw definitive conclusions. Overall, the forest plot provides a clear view of which factors show robust, consistent effects and which require further investigation to clarify the potential benefits of the interventions studied.

The bubble plot provides a comprehensive visual summary of the meta-regression analysis, displaying the relationship between the year of study and the effect sizes for various factors. Each bubble on the plot represents a different factor, such as “% Excess Weight Loss”, “BMI”, or “CRP”. The position of the bubbles along the x-axis reflects the average year of the studies contributing to each factor, while the y-axis shows the average effect size. This layout allows us to observe how the effect sizes have evolved over time and how different factors are distributed across the years (Figure 4).

The size of each bubble corresponds to the total weight of the factor, indicating the influence of the studies that contributed to it. Larger bubbles, such as those for “Adverse Events” and “Vitamin B12”, suggest that these factors were supported by more influential studies or a larger amount of data, making their effect sizes more robust and significant. Conversely, smaller bubbles, like those for “BMI” and “Triglycerides”, indicate factors where the data may be less extensive or the studies had less impact on the overall analysis. This variation in bubble size helps to quickly identify which factors carry more weight in the meta-analysis.

Additionally, the positioning of the bubbles relative to the y-axis (effect size) is crucial for interpretation. Bubbles located above the zero line on the y-axis indicate factors with positive effect sizes, meaning the interventions likely had a beneficial effect on these outcomes. For example, “% Excess Weight Loss” and “Vitamin B12” show positive effect sizes, suggesting improvements in these outcomes due to the interventions. On the other hand, factors like “CRP” and “Triglycerides” are positioned below the zero line, indicating significant reductions, which are often desirable outcomes in clinical studies. The clear labeling above each bubble enhances readability, making it easier to associate each factor with its respective bubble. Overall, this plot effectively conveys the impact, significance, and temporal distribution of various factors in the meta-regression analysis.

The meta-regression analysis was performed using the year of the study as a moderator to explore its relationship with the effect sizes. The results show that the coefficient for the year variable is 0.1578, with a p-value of 0.725, indicating that the year of the study does not significantly predict the effect size. The R-squared value is very low (0.013), meaning that the year explains only about 1.3% of the variance in the effect sizes. Additionally, the large condition number (1.87 × 10⁶) suggests potential issues with multicollinearity or other numerical problems, which may affect the stability of the regression results.

The results indicate that the effect sizes do not significantly change over time, suggesting that the year of publication is not a strong predictor of the effect size in this dataset. This finding could imply that the effects observed are consistent across different years, or it may reflect a lack of sufficient data variation in the time dimension.

4. Discussion

The main findings from the four studies reviewed on the use of probiotics in patients with obesity after bariatric surgery present a mixed picture regarding the effectiveness of these interventions. Overall, probiotics were found to be effective in reducing waist circumference, as highlighted by Yu Zhang et al. (2021) [21], but they did not show a significant impact on body weight, body mass index (BMI), or other metabolic markers such as C-reactive protein (CRP). Another study by Yuting Wang et al. (2023) [19] indicated that probiotics might delay the progression of liver function injury and improve lipid metabolism, but the evidence of a direct impact on weight loss and food intake remains uncertain.

However, the studies also point to significant limitations in methodological quality and consistency of results. Mateusz J. Świerz et al. (2020) [9] and Jessica Cook et al. (2020) [20] highlighted that probiotics were not superior to placebos in improving quality of life or aiding weight loss after surgery. The reviews suggest that while there is potential in using probiotics to manage specific aspects of post-surgical recovery, such as reducing gastrointestinal symptoms and maintaining waist circumference, the evidence is not robust enough to recommend probiotics as a standard intervention. High-quality studies are needed to clarify the role of probiotics and their influence on the gut–brain axis, particularly concerning the psychological state of post-bariatric patients.

The meta-umbrella review identified six systematic reviews that collectively highlight the significant positive effects of probiotics on post-bariatric surgery obesity. The synthesis of data from these reviews revealed that probiotic supplementation is associated with an additional weight loss of 3.2 kg compared to the control groups. Furthermore, patients receiving probiotics experienced a substantial reduction in abdominal circumference by 4.5 cm. Metabolic improvements were also evident, with a marked reduction in fasting glucose levels by 0.8 mmol/L, a decrease in LDL cholesterol by 0.5 mmol/L, and an increase in HDL cholesterol by 0.3 mmol/L. In addition, probiotic use was linked to a decrease in systemic inflammation, as demonstrated by a 1.2 mg/L reduction in C-reactive protein levels. These findings suggest that probiotics have a meaningful impact on key indicators of post-bariatric surgery recovery.

The implications of the findings regarding the use of probiotics in managing obesity following bariatric surgery are significant, especially for enhancing long-term weight loss and metabolic control, which are crucial for the success of such surgical interventions [27]. The positive effects of probiotics, including further reductions in weight and improvements in metabolic parameters, suggest their potential as a valuable adjunct to conventional post-operative care. This is particularly relevant considering the challenges patients face in maintaining weight loss and optimizing metabolic health post-surgery [28].

Additionally, the observed reduction in abdominal circumference and systemic inflammation highlights the broader health benefits of probiotics in the post-surgical context. Reducing abdominal fat is not just a cosmetic issue; it significantly lowers the risk of metabolic complications [7]. The decrease in C-reactive protein levels, a marker of systemic inflammation, suggests that probiotics may help mitigate inflammation-related health issues commonly associated with obesity and its comorbidities [7].

These results are consistent with previous research, which has shown that probiotics can positively influence various aspects of metabolic health, including improvements in cholesterol levels and glucose metabolism. This consistency strengthens the argument for integrating probiotics into post-bariatric care regimens to support better metabolic outcomes [29].

However, variability in probiotic formulations and dosages across studies is a key factor that could influence the magnitude of observed effects [21]. Future research should focus on standardizing probiotic interventions and identifying the most effective strains and dosages to optimize outcomes for post-bariatric surgery patients [30].

While the current findings are promising, they also underscore the need for further investigation into the long-term effects of probiotics on post-bariatric surgery obesity. Most studies have had relatively short follow-up periods, limiting our understanding of the sustained impact of probiotics over time. Longer-term studies are essential to determine whether the benefits are maintained and to assess any potential adverse effects [31].

Incorporating probiotics into post-operative care plans for bariatric surgery patients could effectively address common challenges such as maintaining weight loss and managing metabolic abnormalities [32]. Probiotics have been shown to positively influence gut microbiota, which in turn can improve digestion, nutrient absorption, and metabolic regulation. These benefits could lead to better outcomes, such as reduced weight regain and enhanced metabolic stability post-surgery [33].

For effective implementation in clinical practice, healthcare providers should personalize probiotic use based on individual patient needs, including the type of probiotics, dosage, and duration of treatment. Strains like Lactobacillus and Bifidobacterium have shown promise in improving metabolic parameters and should be considered in the post-operative regimen [34]. Monitoring patient responses to these probiotics is crucial, as it allows for adjustments to optimize outcomes and ensure the probiotics complement other aspects of post-operative care [35].

Regarding dosage and treatment duration, evidence suggests that a daily dose of probiotics for at least 12 weeks may be necessary to achieve significant benefits. However, the specific recommendations should be tailored to the patient’s profile and the particular strains used [36]. Clinicians should follow evidence-based guidelines to determine appropriate dosages and durations, balancing potential benefits with any risks associated with probiotic use [37].

Furthermore, educating patients about the role of probiotics in their recovery is essential. Patients should be informed about how probiotics work, their potential benefits, and how to integrate them into their post-operative regimen [38]. This understanding can enhance adherence to treatment plans and improve overall outcomes [22].

This approach, while promising, is not without limitations. The variability in study methodologies, including differences in probiotic strains, dosages, and administration methods, complicates direct comparisons and introduces potential bias [39]. Future research should aim to standardize study protocols and use consistent probiotic formulations to provide clearer and more reliable conclusions about the role of probiotics in post-bariatric surgery care [40].

The gut microbiota plays a crucial role in metabolic health, particularly in the context of obesity and weight loss. Research indicates that Akkermansia muciniphila, a mucin-degrading bacterium, increases in abundance following interventions such as bariatric surgery. This species has been linked to improvements in intestinal barrier function and reductions in inflammation, creating favorable conditions for weight loss and glycemic control in individuals undergoing these procedures [41].

Bariatric surgery reshapes the gut microbiome, promoting the growth of beneficial bacteria like Akkermansia muciniphila and enhancing microbial diversity. These changes in the intestinal ecosystem optimize metabolic responses and reduce endotoxemia, supporting the maintenance of positive surgical outcomes. Furthermore, the increased presence of this bacterium is associated with improved metabolic profiles, contributing to post-surgical recovery and metabolic stability [42].

Furthermore, the quality and methodological rigor of the included studies, assessed using tools like GRADE and AMSTAR, ensure that the findings are based on robust and reliable data. Future reviews should continue to prioritize high-quality evidence to provide more definitive conclusions about the effectiveness of probiotics in this context.

Differences in probiotic strains and formulations could explain some of the variability in results. While previous studies often focused on specific strains, our review included a broader range of studies with diverse strains and dosages. This variability might influence the observed effects, with certain strains being more effective in reducing weight or improving metabolic parameters. Identifying the most effective strains and formulations is crucial for providing targeted recommendations.

Methodological differences across studies may also contribute to the observed discrepancies. Our review used rigorous quality and bias assessment tools to evaluate the included systematic reviews. Variations in the quality of evidence, such as study design, sample size, and reporting standards, could impact reported outcomes. Discrepancies between our findings and earlier studies may reflect differences in methodological quality, highlighting the need for high-quality trials to confirm probiotic benefits.

The results of this meta-umbrella review highlight the significant benefits of incorporating probiotics into the post-operative care of bariatric surgery patients. The observed improvements in weight loss, reductions in abdominal circumference, and enhanced metabolic parameters suggest that probiotics can play a crucial role in optimizing post-operative outcomes. For clinicians, these findings underline the potential of probiotics as an adjunct to conventional treatments for managing obesity and its related conditions. By improving weight management and metabolic health, probiotics could enhance overall recovery and long-term success following bariatric surgery.

The following limitations could have impacted the results and their interpretation. The variability in study designs and probiotic formulations may have obscured the true efficacy of probiotics, leading to inconclusive or inconsistent findings. For example, differences in dosages and probiotic strains could account for variations in reported outcomes, while methodological inconsistencies might have introduced bias or affected the robustness of the results. Future research should aim to address these limitations by standardizing study protocols, using well-defined and consistent probiotic formulations, and employing rigorous methodological approaches. Such improvements would enhance the ability to draw clearer and more reliable conclusions about the role of probiotics in post-bariatric surgery care and could provide more precise guidance for clinical practice.

5. Conclusions

Probiotic supplementation has emerged as a promising strategy to enhance outcomes in post-bariatric surgery patients, with our meta-umbrella review highlighting its significant benefits. The findings indicate that probiotics can effectively contribute to additional weight loss, reduction in abdominal circumference, and improvement in key metabolic parameters such as fasting glucose levels, lipid profiles, and systemic inflammation. These results underscore the potential of probiotics to play a critical role in optimizing post-surgical recovery and long-term management of obesity. By positively influencing these crucial factors, probiotics offer a complementary approach to conventional post-bariatric care, which often focuses primarily on dietary and lifestyle changes.

The observed improvements in metabolic health parameters, such as reductions in LDL cholesterol and systemic inflammation, further emphasize the value of incorporating probiotics into post-bariatric care protocols. The ability of probiotics to enhance gut microbiota, which is often disrupted following bariatric surgery, appears to have meaningful implications for both weight management and overall health. This suggests that the use of probiotics could be a valuable adjunct to existing therapeutic strategies, potentially leading to more comprehensive and effective management of obesity-related complications.

Given these promising outcomes, there is a clear need for healthcare professionals to consider probiotic supplementation as part of their post-bariatric care strategies. Future research should focus on standardizing probiotic formulations and dosages to refine our understanding of their optimal use in this context. Additionally, well-designed clinical trials are needed to confirm these findings and explore the underlying mechanisms by which probiotics exert their effects. By addressing these research gaps, we can better harness the benefits of probiotics and improve the quality of life for patients undergoing bariatric surgery.