Metabolic-Associated Fatty Liver Disease and Weight Loss After Bariatric Surgery: A Systematic Review and Meta-Analysis

Overview

Journal Obes Surg

Date 2024 Nov 19

PMID 39560894

Authors

Fatima Sabench

Elena Cristina Rusu

Helena Clavero-Mestres

Vicente Arredondo-Prats

Marina Veciana-Molins

Sara Muniz-Piera

Margarita Vives

Carmen Aguilar

Elia Bartra

Marta Paris-Sans

Ajla Alibalic

Maria Teresa Auguet Quintilla

Affiliations

Soon will be listed here.

Abstract

Background: Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and Metabolic Dysfunction-Associated Steatohepatitis (MASH) are increasingly prevalent in patients undergoing bariatric surgery (BS). Understanding their impact on weight loss outcomes after surgery and highlighting the results of surgical techniques such as Roux-en-Y Gastric Bypass (RYGB) and Sleeve Gastrectomy (SG) in relation to the presence of MASH are essential for improving patient management and predicting long-term success.

Methods: A systematic review and meta-analysis were conducted. We searched the PubMed database; inclusion criteria were BS patients with liver impairment data at surgery and weight loss data at follow-up of 6 months or longer. Meta-analyses were conducted using R's meta package, assessing heterogeneity with the I statistic and employing subgroup analyses where necessary.

Results: Out of 1126 eligible studies, 22 were included in the final systematic review. For the MASLD vs. Normal Liver (NL) comparison, no significant difference in BMI change was found at 12 months, but subgroup analysis indicated a possible publication bias (published data vs data collected). In the MASH vs. non-MASH comparison, high heterogeneity was noted at 12 months, and further stratification by surgical technique revealed that SG patients with MASH experienced lower weight loss, approaching statistical significance.

Conclusions: MASLD does not significantly affect short-term weight loss outcomes post-BS, but long-term results show variability. Standardized reporting practices and complete data dissemination are essential for future research to enhance meta-analysis reliability and generalizability.

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