Frontiers in Pharmacology (Oct 2024)
Hypoglycemic activity of Garcinia mangostana L. extracts on diabetes rodent models: A systematic review and network meta-analysis
Abstract
BackgroundDiabetes mellitus is a significant global health issue, and alternative treatments from natural products like Garcinia mangostana L. [Clusiaceae] or GM are being explored for their potential benefits. This study focused on evaluating the hypoglycemic effects of GM on diabetic rodent models.MethodsA comprehensive search was conducted in PubMed, Scopus, and Embase for studies reporting blood glucose levels within 2 weeks as the primary outcome and changes in total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) as secondary outcomes. A network meta-analysis (NMA) was performed to determine the pooled effectiveness of each intervention, estimating the weighted mean difference (WMD) and 95% confidence interval (CI) from both direct and indirect evidence. The surface under the cumulative ranking curve (SURCA) was used to rank the interventions.ResultsTen articles were identified, with nine included for quantitative analysis. All GM extracts showed greater effectiveness than the control in decreasing blood glucose levels within 2 weeks. GM at 200 mg/kg (GM200) was the top-ranked extract for reducing glucose levels beyond 2 weeks and increasing HDL-C levels. The ethanol extract of GM at 200 mg/kg (GME200) was the most effective for blood glucose reduction within 2 weeks and for TC and TG reductions. The methanol extract of GM at 200 mg/kg (GMM200) was the top-ranked extract for LDL-C reductions.ConclusionGM and its extracts demonstrated significant hypoglycemic activity and improvements in lipid profiles in diabetic rodent models, highlighting their potential as therapeutic agents for the prevention and treatment of diabetes mellitus. Further research in human trials is warranted to confirm these findings and establish clinical applications.Clinical trial registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023426254.
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