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LING, PING; LV, JING; YANG, DAIZHI; WANG, CHAOFAN; ZHENG, XUEYING; LUO, SIHUI; YANG, XUBIN; DENG, HONGRONG; XU, WEN; YAN, JINHUA; WENG, JIANPING
Diabetes (New York, N.Y.), 06/2023, Letnik: 72, Številka: Supplement_1Journal Article
Objective: The relationship between glycated hemoglobin (HbA1c) and glucose concentrations was widely explored in patients with diabetes, but all of them excluded pregnancies. The purpose of this study was to derive a best-fitting model to calculate glucose management indicator (GMI) from mean blood glucose (MBG) obtained from continuous glucose monitoring (CGM) among pregnant women with type 1 diabetes mellitus (T1DM). Methods: A total of 272 CGM data and corresponding laboratory HbA1c from 98 pregnant women with T1DM in the CARNATION study were analyzed in this study. CGM data were collected to calculate MBG, time-in-range (TIR), and glycemic variability parameters. The relationships between the MBG and HbA1c during pregnancy, and postpartum were explored. Mix-effect regression analysis with polynomial terms and cross-validation method was conducted to investigate the best-fitting model to calculate GMI from MBG obtained by CGM. Results: The pregnant women had a mean age of 28.91±3.78 years, with a diabetes duration of 8.79±6.18 years and a mean BMI of 21.07±2.48 kg/m2. The HbA1c levels were 6.13±1.02% and 6.41±1.00% during pregnancy and at postpartum (P=0.024). The MBG levels were lower during pregnancy than those at postpartum (6.49±1.11 mmol/L vs 7.11±1.46 mmol/L, P= 0.008). After adjusting the confounders of hemoglobin (Hb), BMI, trimesters, disease duration, MAGE and CV%, we developed a pregnancy-specific GMI-MBG equation: GMI for pregnancy (%) = 0.84-0.28* Trimester+0.08 * BMI in kg/m2 +0.01* Hb in g/mL+ 0.50 * MBG in mmol/L. Conclusion: We derived a pregnancy-specific GMI-MBG equation, which should be recommended for antenatal clinical care. Disclosure P.Ling: None. J.Yan: None. J.Weng: None. J.Lv: None. D.Yang: None. C.Wang: None. X.Zheng: None. S.Luo: None. X.Yang: None. H.Deng: None. W.Xu: None. Funding Science and Technology Planning Project of Guangzhou (202102010154); Shanghai Medical and Health Development Foundation (DMRFP_II_14); National Natural Science Foundation of China (81941022)
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