Acupuncture in treating obesity combined with type 2 diabetes mellitus: A systematic review and meta-analysis of randomized controlled clinical trials

医学 针灸科 随机对照试验 超重 荟萃分析 内科学 肥胖 体质指数 腰围 糖尿病 2型糖尿病 不利影响 临床试验 2型糖尿病 物理疗法 替代医学 内分泌学 病理
作者
Ying Wang,Guang-nan Xu,Renhong Wan,Xin Zhou,Liying Ma,Bing Liu,Yuyan Zhang,Liang Zhou
出处
期刊:Complementary Therapies in Clinical Practice [Elsevier BV]
卷期号:49: 101658-101658 被引量:4
标识
DOI:10.1016/j.ctcp.2022.101658
摘要

and purpose: Most type 2 diabetes mellitus (T2DM) patients are accompanied by overweight or obesity, and it is difficult to concurrently solve these two issues with conventional treatment regimens without experiencing adverse effects. While clinical practice demonstrates that acupuncture is beneficial in treating obesity combined with T2DM, there is a lack of evidence-based medicine to support this claim. The study aims to systematically evaluate the efficacy and safety of acupuncture in treating obesity combined with T2DM.By searching eight electronic databases, we collected randomized controlled trials on acupuncture in treating obesity combined with T2DM. Two reviewers independently screened the literature, extracted the data, and assessed the risk of bias in the included studies. Meta-analysis was then performed using RevMan 5.4 software.A total of 13 randomized controlled trials (RCTs) involving 993 patients were eventually included. Meta-analysis results demonstrated the effective rate of clinical symptoms: [RR = 1.19, 95% CI: 1.11, 1.28, P < 0.00001]; body mass index: [MD = -2.11, 95% CI: -2.56, -1.66, P < 0.00001]; fasting plasma glucose: [MD = -1.09, 95% CI: -1.60, -0.59, P < 0.00001]; haemoglobin A1c: [MD = -0.58, 95% CI: -0.95, -0.20, P = 0.002]; triglyceride: [MD = -0.29, 95% CI: -0.46, -0.11, P = 0.001]; waist circumference: [MD = -5.36, 95% CI: -8.68, -2.05, P = 0.002]; body fat rate: [MD = -3.59, 95% CI: -4.28, -2.90, P < 0.00001].Current evidence suggests that acupuncture has advantages in treating obesity combined with T2DM. However, due to low-quality evidence of included research, additional large-sample and high-quality research are required to validate the findings of this study.
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