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Meta-Analysis
. 2024 Nov 21;22(1):548.
doi: 10.1186/s12916-024-03744-x.

Strategic interventions in clinical randomized trials for metabolic dysfunction-associated steatotic liver disease (MASLD) and obesity in the pediatric population: a systematic review with meta-analysis and bibliometric analysis

Isabel Omaña-Guzmán  1 , Marisol Rosas-Diaz  2 , Yoscelina Estrella Martínez-López  3 , L Monserrat Perez-Navarro  4 , Alvaro Diaz-Badillo  5 , Anthony Alanis  6 , Alejandra Bustamante  7 , Octelina Castillo-Ruiz  8 , Noemi Del Toro-Cisneros  9 , Diego Armando Esquivel-Hernandez  10 , Gloria Garcia-Villalobos  4 , Nayely Garibay-Nieto  1 , Esperanza Milagros Garcia-Oropesa  2 , Juan Carlos Hernandez-Martinez  2 , Elena Beatriz Lopez-Sosa  11 , Carlos Maldonado  12 , David Martinez  13 , Joshua Membreno  6 , Oscar Omar Moctezuma-Chavez  14 , Claudia X Munguia-Cisneros  15 , Edna J Nava-González  16 , Adriana L Perales-Torres  8 , Adolfo Pérez-García  17 , Hector Rivera-Marrero  6 , Alisha Valdez  6 , Alfonso Alejandro Vázquez-Chávez  18 , Carlos Ramirez-Pfeiffer  19 , Kathleen V Carter  6 , Beatriz Tapia  20   21 , Leonel Vela  21 , Juan Carlos Lopez-Alvarenga  22   23
Affiliations
Meta-Analysis

Strategic interventions in clinical randomized trials for metabolic dysfunction-associated steatotic liver disease (MASLD) and obesity in the pediatric population: a systematic review with meta-analysis and bibliometric analysis

Isabel Omaña-Guzmán et al. BMC Med. .

Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is a prevalent hepatic condition linked to metabolic alterations. It gradually causes liver damage and potentially progresses to cirrhosis. Despite its significance, research, especially in the pediatric population, is limited, leading to contradictory findings in diagnosis and treatment. This meta-analysis aims to synthesize existing literature on therapeutic interventions for MASLD in children and adolescents.

Methods: A comprehensive search of randomized controlled clinical trials yielded 634 entries from PubMed, Scopus, and Web of Science up to 2023. Interventions included medications, behavioral modifications, dietary changes, probiotics, supplements, surgical procedures, or combinations. The analysis focused on studies with treatment duration of at least 3 months, employing a random-effects REML meta-analysis model. Treatment effects on anthropometric measurements and biochemical components were examined and adjusted for heterogeneity factors analysis. A bibliometric analysis for insights into research contributors was performed.

Results: The systematic review incorporated 31 clinical trials, with 24 meeting criteria for meta-analysis. These comprised 3 medication studies, 20 with supplements, 4 focusing on lifestyle, and 4 centered on diets. Significant overall treatment effects were observed for ALT, AST, BMI, and HOMA-IR mainly by supplements and lifestyle. Meta-regression identified age, BMI changes, and treatment duration as factors modifying ALT concentrations. Bibliometric analysis involving 31 linked studies highlighted contributions from 13 countries, with the USA, Spain, and Chile being the most influential.

Conclusions: We conclude that supplementation and lifestyle changes can effectively impact ALT and AST levels, which can help address liver issues in obese children. However, the evaluation of risk bias, the high heterogeneity, and the bibliometric analysis emphasize the need for more high-quality studies and broader inclusion of diverse child populations to provide better therapeutic recommendations.

Trial registration: PROSPERO, CRD42023393952. Registered on January 25, 2023.

Keywords: Liver enzymes; MASLD (metabolic dysfunction-associated steatotic liver disease); Meta-analysis; Pediatric NAFLD; Randomized controlled trials; Therapeutic interventions.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: This meta-analysis did not involve any direct interaction with human or animal subjects; it exclusively utilized publicly available data from previously published studies. Consequently, there was no requirement for Institutional Review Board (IRB) approval. The protocol was registered in PROSPERO (CRD42023393952) to ensure methodological transparency and to adhere to best practices in systematic review research. Competing interests: The authors declare that they have no competing interests. They do not work for private laboratories and have not received any payments.

Figures

Fig. 1
Fig. 1
PRISMA 2009 flow diagram for study selection
Fig. 2
Fig. 2
Risk of bias assessment. Low risk of bias (green) indicates that the study has a low likelihood of bias affecting the results. Unclear risk of bias (yellow) indicates insufficient information to determine the risk of bias. A high risk of bias (red) indicates that there is a high likelihood that bias could have influenced the study’s results. The right column shows treatment’s groups. Using multiple combinations of interventions increases the complexity and does not allow blindness implementation
Fig. 3
Fig. 3
Forest plot of ALT levels using random effects model. Panel A shows the treatment’s overall effect was small to medium (Cohen-d − 0.34 95%CI − 0.65, − 0.03). Most studies showed the effect on improving the ALT concentration. Panel B shows the overall adjusted size of the effect remained the same with smaller 95% confidence intervals
Fig. 4
Fig. 4
Forest plot of AST levels using random effects model. Panel A shows medium effect on AST. Panel B shows less uncertainty with smaller confidence intervals
Fig. 5
Fig. 5
Forest plot of BMI using random effects model. Panel A shows the overall effect on BMI was small (Cohen-d = − 0.27 (95%CI − 0.55, 0.01) p = 0.06. Michelli, et al. [32] has the highest size of effect, more than 3 standard deviations of difference. This big difference was attributed to differences in the opposite effects of placebo vs. active treatment. Panel B showed adjusted values diminishing the variation of Michelli study and increasing precision in the 95% confidence interval
Fig. 6
Fig. 6
Forest plot of HOMA-IR calculation using random effects model. Panel A shows treatments had small to medium effect on HOMA-IR levels. Panel B shows increased precision with adjusted size of effects with smaller 95% confidence intervals
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