scholarly journals Critically Appraised Papers: An aerobic and resistance exercise program can improve glycaemic control in women with gestational diabetes mellitus [commentary]

2018 ◽  
Vol 64 (2) ◽  
pp. 124
Author(s):  
Anne Harrison
Author(s):  
Tineke J Crawford ◽  
Julie Brown ◽  
Jane Alsweiler ◽  
Ruth Martis ◽  
Caroline A Crowther

2010 ◽  
pp. 2133-2139 ◽  
Author(s):  
Moshe Hod ◽  
Yariv Yogev

Diabetes is one of the most common medical complications in pregnancy: 0.4 to 2% of all births are complicated by pregestational diabetes; about 3% of pregnancies are complicated by gestational diabetes mellitus, with substantially more in some populations. Preconceptional evaluation—this should include evaluation of glycaemic control, blood pressure, retinal disease, renal status, thyroid function, peripheral and autonomic neuropathy, peripheral vascular disease, and hypoglyacemic symptoms....


Author(s):  
Martina Gáborová ◽  
Viera Doničová ◽  
Ivana Bačová ◽  
Mária Pallayová ◽  
Martin Bona ◽  
...  

Background: The aim of the study was to compare the continuous glucose monitoring (CGM)-determined glycaemic variability (GV) of pregnant women with gestational diabetes mellitus (GDM) and without GDM (CG; control group). The secondary aim was to evaluate the association between risk factors of diabetes in pregnancy and parameters of glyceamic control. Methods: Demographic, biometric and biochemical parameters were obtained for pregnant women (20–38 years old) who after an oral glucose tolerance test were examined by 7-day continuous glucose monitoring using a iPro®2 Professional CGM. Results: The differences in GV between women with GDM and CG compared by total area under glucose curve (total AUC, (mmol·day/L) was statistically significant (p = 0.006). Other parameters of glycaemic control such as mean glucose, standard deviation, coefficient of variation, J-index, % time-above target range 7.8 mmol/L (%TAR), % time-in range 3.5–7.8 mmol/L (%TIR), time-below target range 3.5 mmol/L (%TBR), glycated haemoglobin were not significantly different in the study groups. Risk factors (a family history of diabetes, pre-pregnancy BMI, higher weight gain and age) correlated with parameters of glycaemic control. Conclusions: We found a significant difference in GV of women with and without GDM by total AUC determined from CGM. TIR metrics were close to significance. Our work points at an increased GV in relation to the risk factors of GDM. Pregnant women with risk factors have higher probability of severe GV with its consequences on maternal and fetal health state.


2013 ◽  
Vol 37 ◽  
pp. S49
Author(s):  
Faith Delos-Reyes ◽  
Jennifer Price ◽  
Mireille Landry ◽  
Ananya Banerjee ◽  
Lorraine Lipscombe

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