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Glycaemia dynamics in gestational diabetes mellitus
Paola Valero1, Rodrigo Salas2, Fabián Pardo3
1Cellular and Molecular Physiology Laboratory (CMPL), Department of Obstetrics, Division of Obstetrics and Gynaecology, School of Medicine, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago 8330024, Chile; Faculty of Health Sciences, Universidad de Talca, Talca 3460000, Chile.
Gestational diabetes mellitus (GDM) in pregnant women requires careful blood glucose management. Understanding glycaemia dynamics, or glucose variation, is crucial for improving pregnancy outcomes and preventing complications.
Area of Science:
- Obstetrics and Gynecology
- Endocrinology
- Perinatal Medicine
Background:
- Gestational diabetes mellitus (GDM) is characterized by maternal and fetal hyperglycemia, posing risks to mother, fetus, and newborn.
- Maternal hyperglycemia in GDM can lead to fetoplacental endothelial dysfunction.
- Controlling both chronic and acute glucose fluctuations is vital for mitigating GDM's harmful effects.
Purpose of the Study:
- To review metrics for assessing glycaemia dynamics in gestational diabetes mellitus.
- To explore the application of these metrics in understanding pregnancy outcomes.
- To discuss the utility of self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) data.
Main Methods:
- Review of quantitative metrics for glycaemia dynamics.
- Analysis of metrics derived from plane distribution, amplitude, score values, and variability estimation.
- Consideration of time series analysis for glucose variation.
Main Results:
- Various metrics can quantify glycaemia dynamics, reflecting blood glucose handling.
- These metrics offer insights into the impact of glucose fluctuations.
- Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) data can be utilized.
Conclusions:
- Understanding glycaemia dynamics is essential for managing GDM.
- Metrics derived from SMBG and CGM hold potential for assessing pregnancy outcomes in GDM.
- Further application of these metrics can aid in preventing adverse pregnancy outcomes.
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