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The safety and efficacy of Momordica charantia L. in animal models of type 2 diabetes mellitus: A systematic review and meta‐analysis
Author(s) -
Peter Emanuel L.,
Nagendrappa Prakash B.,
Kaligirwa Anita,
Ogwang Patrick Engeu,
Sesaazi Crispin Duncan
Publication year - 2021
Publication title -
phytotherapy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.019
H-Index - 129
eISSN - 1099-1573
pISSN - 0951-418X
DOI - 10.1002/ptr.6853
Subject(s) - medicine , glycemic , momordica , diabetes mellitus , insulin resistance , meta analysis , type 2 diabetes , type 2 diabetes mellitus , insulin , blinding , cinahl , pharmacology , traditional medicine , endocrinology , randomized controlled trial , psychiatry , psychological intervention
Type 2 diabetes mellitus is a chronic hyperglycemic condition due to progressively impaired glucose regulation. Momordica charantia L. could potentially improve hyperglycemia because its fruit extracts can alleviate insulin resistance, beta‐cell dysfunction, and increase serum insulin level. We evaluated the effect of M. charantia L. in comparison with a vehicle on glycemic control in animal models of type 2 diabetes mellitus. MEDLINE, Web of Science, Scopus, and CINAHL databases were searched without language restriction through April 2019. About 66 studies involving 1861 animals that examined the effect of M. charantia L. on type 2 diabetes mellitus were included. Fruits and seed extracts reduced fasting plasma glucose (FPG) and glycosylated hemoglobin A1c in comparison to vehicle control: (42 studies, 815 animals; SMD, −6.86 [95% CI; −7.95, −5.77], 3 studies, 59 animals; SMD; −7.76 [95% CI; −12.50, −3.01]) respectively. Also, the extracts have hepato‐renal protective effects at varying doses and duration of administration. Despite the observed significant glycemic control effect, poor methodological quality calls for future researches to focus on standardizing extract based on chemical markers and adopt measures to improve the quality of preclinical studies such as sample size calculation, randomization, and blinding.