Participant characteristics in the prevention of gestational diabetes as evidence for precision medicine: a systematic review and meta-analysis. Journal Articles uri icon

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abstract

  • BACKGROUND: 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. METHODS: 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. RESULTS: From 10347 studies, 116 studies (nā€‰=ā€‰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. CONCLUSIONS: 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.

authors

  • de Souza, Russell
  • Sherifali, Diana
  • 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 KW
  • Liu, Kai
  • Mekonnen, Eskedar Getie
  • Pathirana, Maleesa
  • Quinteros, Alejandra
  • Taylor, Rachael
  • Ukke, Gebresilasea G
  • Zhou, Shao J
  • ADA/EASD PMDI
  • Josefson, Jami

publication date

  • October 5, 2023