Objective: Glucose management indicator (GMI) is a core metric derived from continuous glucose monitoring (CGM) and is widely used to evaluate glucose control in patients with diabetes. No study has explored the pregnancy-specific GMI. This study aimed to derive a best-fitting model to calculate GMI from mean blood glucose (MBG) obtained from 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 analysed in this study. Continuous glucose monitoring data were collected to calculate MBG, time-in-range (TIR), and glycaemic 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 28.9 ± 3.8 years, with a diabetes duration of 8.8 ± 6.2 years and a mean body mass index (BMI) of 21.1 ± 2.5 kg/m . The HbA1c levels were 6.1 ± 1.0% and 6.4 ± 1.0% during pregnancy and at postpartum (p = 0.024). The MBG levels were lower during pregnancy than those at postpartum (6.5 ± 1.1 mmol/L vs. 7.1 ± 1.5 mmol/L, p = 0.008). After adjusting the confounders of haemoglobin (Hb), BMI, trimesters, disease duration, mean amplitude of glycaemic excursions and CV%, we developed a pregnancy-specific GMI-MBG equation: GMI for pregnancy (%) = 0.84-0.28* [Trimester] + 0.08 * [ BMI in kg/m ] + 0.01 * [Hb in g/mL] + 0.50 * [MBG in mmol/L].
Conclusions: We derived a pregnancy-specific GMI equation, which should be recommended for antenatal clinical care.
Clinical Trial Registry Number: ChiCTR1900025955.
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http://dx.doi.org/10.1002/dmrr.3689 | DOI Listing |
J Nutr Educ Behav
January 2025
School of Medicine, University of Queensland, Brisbane, Queensland, Australia; Women's and Newborn Services, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
Objective: To explore the context, behaviors, strategies, and motivators of pregnant women who consume 5 servings of vegetables daily.
Methods: Positive deviance study involving Australian pregnant women (9 of 529) identified through a validated food frequency questionnaire. Semistructured interviews explored their strategies, behaviors, and motivators.
Ann Med
December 2025
Department of Laboratory Medicine, The Women's Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Objective: The process of glycolysis from blood collection to centrifugation impacts the diagnosis of gestational diabetes mellitus (GDM). However, the specific characteristics of the working environment in China and its influence on GDM diagnosis still need to be clarified.
Methods: Firstly, 15 pregnant women were recruited, and six specimens were collected from each in a fasting state.
J Diabetes Investig
January 2025
Department of Obstetrics and Gynecology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
Aims: This study investigated the association between maternal age and early and late gestational diabetes mellitus (GDM).
Methods: In total, 72,270 pregnant women were included in this prospective birth cohort study. Associations between maternal age and early GDM (diagnosed at <24 gestational weeks) and late GDM (diagnosed at ≥24 gestational weeks) were evaluated using a multinomial logistic regression model with possible confounding factors.
Hum Vaccin Immunother
December 2025
School of Public Health, Peking University, Beijing, China.
The attitudes of reproductive-age individuals toward COVID-19 vaccination during pregnancy are still not well understood. We aimed to explore the attitudes toward COVID-19 vaccines during pregnancy and the determinants among the Chinese reproductive-age population. An anonymous cross-sectional study was conducted in China from July 4 to August 11, 2023.
View Article and Find Full Text PDFArch Dis Child
December 2024
Research Department of Behavioural Science and Health, University College London, London, UK.
Objectives: To understand (1) healthcare professionals' (HCPs) perceptions and experiences of commercial milk formula (CMF) marketing to consumers and HCPs and (2) HCPs' perspectives on regulation of CMF marketing.
Setting: UK.
Design: In-person and online interviews with 41 HCPs with regular contact with pregnant women and mothers.
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