Chen Dandan, Ye Zhihong, Shao Jing, Tang Leiwen, Zhang Hui, Wang Xiyi, Qiu Ruolin, Zhang Qi
Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
BMJ Open. 2020 Oct 8;10(10):e036927. doi: 10.1136/bmjopen-2020-036927.
We aimed to examine whether eHealth interventions can effectively improve anthropometric and biochemical indicators of patients with metabolic syndrome (MetS).
Systematic review and meta-analysis.
PubMed, the Web of Science, Embase, Medline, CINAHL, PsycINFO, the Cochrane Library, the Chinese National Knowledge Infrastructure, the Wanfang and Weipu databases were comprehensively searched for papers that were published from database inception to May 2019. Articles were included if the participants were metabolic syndrome (MetS) patients, the participants received eHealth interventions, the participants in the control group received usual care or were wait listed, the outcomes included anthropometric and biochemical indicators of MetS, and the study was a randomised controlled trial (RCT) or a controlled clinical trial (CCT). The Quality Assessment Tool for Quantitative Studies was used to assess the methodological quality of the included articles. The meta-analysis was conducted using Review Manager V.5.3 software.
In our review, seven RCTs and two CCTs comprising 935 MetS participants met the inclusion criteria. The results of the meta-analysis revealed that eHealth interventions resulted in significant improvements in body mass index (standardised mean difference (SMD)=-0.36, 95% CI (-0.61 to -0.10), p<0.01), waist circumference (SMD=-0.47, 95% CI (-0.84 to -0.09), p=0.01) and systolic blood pressure(SMD=-0.35, 95% CI (-0.66 to -0.04), p=0.03) compared with the respective outcomes associated with the usual care or wait-listed groups. Based on the included studies, we found significant effects of the eHealth interventions on body weight. However, we did not find significant positive effects of the eHealth interventions on other metabolic parameters.
The results indicated that eHealth interventions were beneficial for improving specific anthropometric outcomes, but did not affect biochemical indicators of MetS. Therefore, whether researchers adopt eHealth interventions should be based on the purpose of the study. More rigorous studies are needed to confirm these findings.
我们旨在研究电子健康干预措施能否有效改善代谢综合征（MetS）患者的人体测量和生化指标。
系统评价和荟萃分析。
全面检索了PubMed、科学网、Embase、Medline、CINAHL、PsycINFO、Cochrane图书馆、中国知网、万方和维普数据库，查找从数据库建立至2019年5月发表的论文。纳入标准为：参与者为代谢综合征（MetS）患者；参与者接受电子健康干预；对照组参与者接受常规护理或等待名单处理；结局包括MetS的人体测量和生化指标；研究为随机对照试验（RCT）或对照临床试验（CCT）。采用定量研究质量评估工具评估纳入文章的方法学质量。使用Review Manager V.5.3软件进行荟萃分析。
在我们的综述中，7项RCT和2项CCT（共935名MetS参与者）符合纳入标准。荟萃分析结果显示，与常规护理或等待名单组的相应结局相比，电子健康干预在体重指数（标准化均数差（SMD）=-0.36，95%CI（-0.61至-0.10），p<0.01）、腰围（SMD=-0.47，95%CI（-0.84至-0.09），p=0.01）和收缩压（SMD=-0.35，95%CI（-0.66至-0.04），p=0.03）方面有显著改善。基于纳入的研究，我们发现电子健康干预对体重有显著影响。然而，我们未发现电子健康干预对其他代谢参数有显著的积极影响。
结果表明，电子健康干预有利于改善特定的人体测量结局，但不影响MetS的生化指标。因此，研究人员是否采用电子健康干预应基于研究目的。需要更严谨的研究来证实这些发现。
