Decreased complexity of glucose time series index associated with adverse pregnancy outcomes in gestational diabetes mellitus

医学 妊娠期糖尿病 优势比 置信区间 怀孕 产科 胎龄 逻辑回归 混淆 糖尿病 内科学 妊娠期 内分泌学 遗传学 生物
作者
Guiling Liang,Mengyu Lai,Yaxin Wang,Na Li,Mei Kang,Jingyi Lu,Yanmei Su,Fang Fang,Yongde Peng,Xianming Xu,Jianrong Weng,Jian Zhou,Yufan Wang
出处
期刊:Diabetes, Obesity and Metabolism [Wiley]
标识
DOI:10.1111/dom.15698
摘要

Abstract Aim We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). Materials and Methods In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32‐3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. Results Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41‐33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04‐39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). Conclusion A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.
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