Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China.
Diabetes Obes Metab. 2024 Sep;26(9):3587-3596. doi: 10.1111/dom.15698. Epub 2024 Jun 21.
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).
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.
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).
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.
本研究旨在探讨妊娠期间血糖时间序列复杂度指数（CGI）与妊娠期糖尿病（GDM）女性不良妊娠结局之间的关系。
在这项回顾性队列研究中，388 例 GDM 单胎妊娠女性在中位数为 26.86 孕周时接受连续血糖监测（CGM）。CGI 是根据 CGM 数据采用精细复合多尺度熵计算得出的。根据基线 CGI（CGI<2.32、2.32-3.10、≥3.10）将参与者分为三分位。采用 logistic 回归评估 CGI 与复合不良结局或巨大儿（LGA）之间的关系。采用受试者工作特征分析评估 CGI 的鉴别性能。
在 388 名参与者中，71 名（18.3%）新生儿为 LGA，63 名（16.2%）发生复合不良结局。在调整混杂因素后，与高 CGI（CGI≥3.10）组相比，低 CGI（CGI<2.32）组复合不良结局的发生风险更高（比值比：12.10，95%置信区间：4.41-33.18）和 LGA（比值比：12.68，95%置信区间：4.04-39.75）。根据受试者工作特征分析，CGI 对预测不良妊娠结局的能力明显优于糖化血红蛋白和传统 CGM 指标（均 p<0.05）。
妊娠期间 CGI 较低与复合不良结局和 LGA 相关。CGI 作为一种新的血糖稳态预测指标，似乎优于传统的葡萄糖指标，可用于预测 GDM 女性的不良妊娠结局。
