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Un nuevo estudio señala que el ajo es muy potente para reducir el azúcar y el colesterol en sangre

In a recent study published in the journal Nutrients, a group of researchers in China conducted a systematic review and meta-analysis to investigate the effects of garlic on blood lipid and glucose levels in humans.


Chronic non-communicable diseases, including cardiovascular diseases, chronic respiratory diseases, cancers, and diabetes, cause 41 million deaths annually. Glucose and lipids are crucial for energy, and their dysregulation can lead to atherosclerosis, diabetes, and fatty liver disease. Dyslipidemia, with high total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and low high-density lipoprotein cholesterol (HDL-C), is a major cardiovascular risk factor. Current treatments for metabolic diseases focus on symptom relief and have side effects. Garlic, rich in compounds like allicin, shows potential in regulating glucose and lipids. Further research is needed to understand its mechanisms, optimal dosage, and long-term effects.

About the study

In the present study, four databases- Embase, PubMed, Cochrane Library, and Web of Science were searched up to February 2024 using terms related to garlic, glucose, and lipid metabolism. Additional eligible trials were identified through manual searches, and the study adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020. Inclusion criteria were randomized clinical trials over two weeks, reporting outcomes like Hemoglobin A1c (HbA1c), fasting blood glucose (FBG), TC, HDL-C, LDL-C, and TG, involving adults aged 18 or older, with a placebo control group. Exclusions included non-garlic interventions, combined supplements, pregnant participants, non-clinical studies, and incomplete data.

Two researchers independently extracted data, including study details, sample size, demographics, and mean and standard deviation values for glucose and lipid indicators. Study quality was assessed using Cochrane Collaboration tools, evaluating bias risk factors.

Data analysis involved converting glycated hemoglobin units and standardizing blood glucose and lipid levels. Mean outcome changes were calculated from baseline and endpoint data, assessing heterogeneity with chi-square tests and the I2 index. Significant heterogeneity led to using a random-effects model with a significance threshold of 0.05. Subgroup analyses and sensitivity analyses were conducted to explore heterogeneity sources and the impact of individual studies. Publication bias was evaluated using funnel plots and Egger's test, with trim and fill analysis for stability assessment.

Source: News Medical Today

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