Participant characteristics in the prevention of gestational diabetes as evidence for precision medicine: a systematic review and meta-analysis.
Participant characteristics in the prevention of gestational diabetes as evidence for precision medicine: a systematic review and meta-analysis.
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DOI：
10.1038/s43856-023-00366-x
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发表时间：
2023-10-05
期刊：
影响因子：
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通讯作者：
Josefson, Jami
中科院分区：
文献类型：
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作者：
Lim, Siew;Takele, Wubet Worku;Vesco, Kimberly K;Redman, Leanne M;Hannah, Wesley;Bonham, Maxine P;Chen, Mingling;Chivers, Sian C;Fawcett, Andrea J;Grieger, Jessica A;Habibi, Nahal;Leung, Gloria K W;Liu, Kai;Mekonnen, Eskedar Getie;Pathirana, Maleesa;Quinteros, Alejandra;Taylor, Rachael;Ukke, Gebresilasea G;Zhou, Shao J;Josefson, Jami
精准预防涉及利用特定群体的独特特征来确定他们对预防性干预措施的反应。本研究的目的是系统地评估参与者的特点与反应的干预措施，在妊娠期糖尿病（GDM）的预防。我们检索了MEDLINE、EMBASE和Pubmed，以确定截至2022年5月24日发表的GDM预防的生活方式（饮食、体力活动或两者兼而有之）、二甲双胍、肌醇/肌醇和益生菌干预措施。从10347项研究中，纳入了116项研究（n = 40940名女性）。与肥胖BMI相比，身体活动导致基线时体重指数（BMI）正常的参与者GDM减少更多（风险比，95%置信区间：0.06 [0.03，0.14] vs 0.68 [0.26，1.60]）。饮食和体力活动相结合的干预措施使无多囊卵巢综合征（PCOS）的参与者比PCOS患者更能减少GDM（0.62 [0.47，0.82] vs 1.12 [0.78-1.61]），无GDM病史的患者比GDM病史不明的患者（0.62 [0.47，0.81] vs 0.85 [0.76，0.95]）。在PCOS患者中，二甲双胍干预比状态不明的患者更有效（0.38 [0.19，0.74] vs 0.59 [0.25，1.43]），或者在孕前开始时比在妊娠期间更有效（0.21 [0.11，0.40] vs 1.15 [0.86-1.55]）。产次、有过大于胎龄儿史或糖尿病家族史对干预反应没有影响。通过二甲双胍或生活方式预防GDM根据某些个体特征而有所不同。未来的研究应包括从孕前开始的试验，并提供按先验定义的参与者特征（包括社会和环境因素、临床特征和其他新的风险因素）分类的结果，以预测通过干预措施预防GDM。一个人的特征，如医学，生物化学，社会和行为可能会影响他们对旨在预防妊娠期糖尿病的干预措施的反应。在这里，我们评估了已发表的关于饮食、生活方式、药物治疗和营养补充等干预措施的文献，并研究了哪些个体参与者特征与对这些干预措施的反应相关。某些参与者的特征与通过特定治疗更好地预防妊娠期糖尿病有关。一些干预措施在受孕前开始更有效。未来的研究在评估预防措施的效果时应考虑个体特征。Lim等人进行了一项系统综述和荟萃分析，以确定与妊娠期糖尿病预防反应相关的参与者特征。BMI、多囊卵巢综合征和处于孕前阶段等特征可以决定对某些预防性干预措施的反应。
Precision prevention involves using the unique characteristics of a particular group to determine their responses to preventive interventions. This study aimed to systematically evaluate the participant characteristics associated with responses to interventions in gestational diabetes mellitus (GDM) prevention. We searched MEDLINE, EMBASE, and Pubmed to identify lifestyle (diet, physical activity, or both), metformin, myoinositol/inositol and probiotics interventions of GDM prevention published up to May 24, 2022. From 10347 studies, 116 studies (n = 40940 women) are included. Physical activity results in greater GDM reduction in participants with a normal body mass index (BMI) at baseline compared to obese BMI (risk ratio, 95% confidence interval: 0.06 [0.03, 0.14] vs 0.68 [0.26, 1.60]). Combined diet and physical activity interventions result in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) than those with PCOS (0.62 [0.47, 0.82] vs 1.12 [0.78–1.61]) and in those without a history of GDM than those with unspecified GDM history (0.62 [0.47, 0.81] vs 0.85 [0.76, 0.95]). Metformin interventions are more effective in participants with PCOS than those with unspecified status (0.38 [0.19, 0.74] vs 0.59 [0.25, 1.43]), or when commenced preconception than during pregnancy (0.21 [0.11, 0.40] vs 1.15 [0.86–1.55]). Parity, history of having a large-for-gestational-age infant or family history of diabetes have no effect on intervention responses. GDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results disaggregated by a priori defined participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions. An individual’s characteristics, such as medical, biochemical, social, and behavioural may affect their response to interventions aimed at preventing gestational diabetes, which occurs during pregnancy. Here, we evaluated the published literature on interventions such as diet, lifestyle, drug treatment and nutritional supplement and looked at which individual participant characteristics were associated with response to these interventions. Certain participant characteristics were associated with greater prevention of gestational diabetes through particular treatments. Some interventions were more effective when started prior to conception. Future studies should consider individual characteristics when assessing the effects of preventative measures. Lim et al. perform a systematic review and meta-analysis to identify participant characteristics associated with response to gestational diabetes prevention. Characteristics such as BMI, polycystic ovary syndrome and being in the preconception phase could determine responses to certain preventive interventions.