Continuous Glucose Monitoring in Pregnancy: New Frontiers in Clinical Applications and Research

Sung, Joyce F.; Taslimi, M. Mark; Faig, J.

doi:10.1177/193229681200600629

Cited by 9 publications

(5 citation statements)

References 47 publications

(65 reference statements)

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“…It has been shown that continuous glucose monitoring (CGM) is useful for evaluating glycemic control during pregnancy [14]. In the present study, we determined the mean blood glucose (MBG) by conducting CGM in pregnant women with diabetes to examine whether HbA1c and GA show a close correlation with MBG or not.…”

Section: Introductionmentioning

confidence: 97%

Hemoglobin A1C but not Glycated Albumin Overestimates Glycemic Control due to Iron Deficiency in Pregnant Women with Diabetes

Moriya¹

2014

J Diabetes Metab

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Background: Pregnant women are frequently complicated with iron deficiency. Because Hemoglobin A1c (HbA1c) shows an apparently high value in patients with iron-deficiency, HbA1c was reported to be elevated due to iron deficiency in pregnant women with or without diabetes. In the present study, we investigated whether HbA1c or Glycated Albumin (GA) accurately reflects glycemic control state estimated from the Mean Blood Glucose (MBG) obtained by Continuous Glucose Monitoring (CGM) in pregnant women with diabetes. Methods: We studied 20 pregnant women with diabetes whose glycemic control was stable and CGM was performed to determine MBG. The estimated HbA1c and GA were calculated from the MBG, and the measured values were compared with the estimated values. Correlations between Mean Corpuscular Hemoglobin (MCH), an index of iron-deficiency, and continuous variables were examined. Results: HbA1c was not significantly correlated with GA. The measured GA was not significantly different from the estimated GA (16.0 ± 2.7% vs. 16.0 ± 1.8%, P=0.982). On the other hand, the measured HbA1c was significantly higher than the estimated HbA1c [6.4 ± 0.9% (46.3 ± 10.3 mmol/mol) vs. 5.6 ± 0.5% (38.2 ± 5.4 mmol/mol), P<0.001]. The measured HbA1c (R=-0.598, P=0.005) and the measured HbA1c/estimated HbA1c ratio (R=-0.566, P=0.009) showed significant inverse correlations with MCH. Conclusions: HbA1c overestimates glycemic control due to iron deficiency in pregnant women with diabetes, whereas GA accurately reflected their glycemic control. Therefore, GA is a better index of glycemic control than HbA1c in pregnant women with diabetes. J ou rna l o f D ia be tes & M e ta bolism

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Section: Introductionmentioning

confidence: 97%

Hemoglobin A1C but not Glycated Albumin Overestimates Glycemic Control due to Iron Deficiency in Pregnant Women with Diabetes

Moriya¹

2014

J Diabetes Metab

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“…Second, we estimated HbA1c and GA using MBG obtained from the diurnal variation, not by continuous glucose monitoring (CGM), which is more accurate for evaluating glycaemic control. 28 Third, the adjGA has not been generalized in this population. Fourth, we did not show any reliable data of long-term glycaemic control except for HbA1c or GA. Further, the GA/HbA1c ratio might show the significant diversity in diabetic patients.…”

Section: Discussionmentioning

confidence: 99%

Serum albumin-adjusted glycated albumin is a better indicator of glycaemic control in diabetic patients with end-stage renal disease not on haemodialysis

et al. 2015

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Backgrounds: Diabetic patients with end-stage renal disease who are not on haemodialysis show low concentrations of HbA1c and glycated albumin due to renal anaemia and proteinuria, respectively. In the present study, we examined whether serum albumin-adjusted glycated albumin could accurately reflect glycaemic control in these patients. Methods: To examine the correlation between glycated albumin and serum albumin (Study 1), 49 diabetic patients with end-stage renal disease not on haemodialysis were used. To evaluate the association between the glycaemic control indicators and the glycaemic control state (Study 2), 30 diabetic patients with end-stage renal disease were enrolled. The estimated HbA1c and the estimated glycated albumin concentrations were calculated based on the mean blood glucose concentrations obtained from the diurnal variation. The adjusted glycated albumin concentrations were calculated from the regression formula between the serum albumin and glycated albumin obtained from Study 1. Results: No significant correlation was found between the measured HbA1c and estimated HbA1c concentrations. The estimated HbA1c (inversely) and measured HbA1c/estimated HbA1c ratio (positively), but not measured HbA1c, showed a significant correlation with Hb concentrations. The estimated glycated albumin was positively associated with the measured glycated albumin and adjusted glycated albumin concentrations. Although measured glycated albumin/estimated glycated albumin ratio was positively correlated with serum albumin, there was no significant association between the adjusted glycated albumin/estimated glycated albumin ratio and serum albumin, Hb and estimated glomerular filtration rate. Conclusions: We found for the first time that the adjustment of glycated albumin by serum albumin could be useful to determine glycaemic control in diabetic patients with end-stage renal disease not on haemodialysis. These findings suggest that adjusted glycated albumin might be a better indicator of glycaemic control than measured HbA1c and measured glycated albumin in these patients.

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“… 5–11 Continuous glucose monitoring (CGM) systems measure interstitial glucose levels by implanting a sensor subcutaneously. 12 Typically, finger prick blood glucose measurements are needed to calibrate the interstitial glucose levels to capillary blood glucose levels, although devices that do not need this calibration step are now becoming increasingly available. 12 , 13 Throughout this paper we refer to the sensor predicted capillary glucose levels as ‘sensor glucose’.…”

Section: Introductionmentioning

confidence: 99%

GLU: a software package for analysing continuously measured glucose levels in epidemiology

Millard

Patel

Tilling

et al. 2020

International Journal of Epidemiology

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Continuous glucose monitors (CGM) record interstitial glucose levels ‘continuously’, producing a sequence of measurements for each participant (e.g. the average glucose level every 5 min over several days, both day and night). To analyse these data, researchers tend to derive summary variables such as the area under the curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data. GLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC and proportion of time spent in hypo-, normo- and hyper- glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user. GLU is implemented in R and is available on GitHub at https://github.com/MRCIEU/GLU. Git tag v0.2 corresponds to the version presented here.

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Continuous Glucose Monitoring in Pregnancy: New Frontiers in Clinical Applications and Research

Cited by 9 publications

References 47 publications

Hemoglobin A1C but not Glycated Albumin Overestimates Glycemic Control due to Iron Deficiency in Pregnant Women with Diabetes

Hemoglobin A1C but not Glycated Albumin Overestimates Glycemic Control due to Iron Deficiency in Pregnant Women with Diabetes

Serum albumin-adjusted glycated albumin is a better indicator of glycaemic control in diabetic patients with end-stage renal disease not on haemodialysis

GLU: a software package for analysing continuously measured glucose levels in epidemiology

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