Non-glycemic-dependent reduction of late pregnancy A1C levels in women with type 1 diabetes

Flash glucose monitoring system in special situations

The management of diabetes mellitus (DM) requires maintaining glycemic control, and patients must keep their blood glucose levels close to the normal range to reduce the risk of microvascular complications and cardiovascular events. While glycated hemoglobin (A1C) is currently the primary measure for glucose management and a key marker for long-term complications, it does not provide information on acute glycemic excursions and overall glycemic variability. These limitations may even be higher in some special situations, thereby compromising A1C accuracy, especially when wider glycemic variability is expected and/or when the glycemic goal is more stringent. To attain adequate glycemic control, continuous glucose monitoring (CGM) is more useful than self-monitoring of blood glucose (SMBG), as it is more convenient and provides a greater amount of data. Flash Glucose Monitoring (isCGM /FGM) is a widely accepted option of CGM for measuring interstitial glucose levels in individuals with DM. However, its application under special conditions, such as pregnancy, patients on hemodialysis, patients with cirrhosis, during hospitalization in the intensive care unit and during physical exercise has not yet been fully validated. This review addresses some of these specific situations in which hypoglycemia should be avoided, or in pregnancy, where strict glycemic control is essential, and the application of isCGM/FGM could alleviate the shortcomings associated with poor glucose control or high glycemic variability, thereby contributing to high-quality care.

Relationship Between Time-in-Range, HbA1c, and the Glucose Management Indicator in Pregnancies Complicated by Type 1 Diabetes

Objective: We aimed to evaluate relationships between time-in-range (TIR 63-140 mg/dL), glycated hemoglobin A1c (HbA1c) level, and the glucose management indicator (GMI) in pregnant women with type 1 diabetes. Research Design and Methods: Continuous glucose monitoring (CGM) data from 27 women with type 1 diabetes were collected prospectively throughout pregnancy. Up to 90-days of CGM data were correlated with point-of-care HbA1c levels measured in the clinic at each trimester. GMI levels were calculated using a published regression formula. Liner models were used to compare TIR, HbA1c, and GMI by each trimester. Results: There was a significant negative correlation between TIR and HbA1c; each 10% increase in TIR was associated with a 0.3% reduction in HbA1c. The correlation between TIR and HbA1c was stronger (r = -0.8) during the second and third trimesters than during the first trimester (r = -0.4). There was good correlation between TIR and GMI during each trimester (r = 0.9 for each trimester). The relationship between GMI and HbA1c especially during second (r = 0.8) and third trimesters (r = 0.8) was strong. Conclusion: In the first trimester, the correlation between HbA1c level and TIR was relatively small, while that of TIR and GMI was very strong, thus GMI may better reflect glycemic control than HbA1c in early pregnancy. Each 10% increase in TIR was associated with a 0.3% reduction in HbA1c throughout pregnancy, which was lower than other published studies in nonpregnant populations reporting a 0.5%-0.8% reduction in HbA1c. Further studies are needed to understand the relationship between TIR and GMI and how GMI may affect maternal and fetal complications. Clinical Trial Registration number: NCT02556554.

Third trimester HbA1c and the association with large-for-gestational-age neonates in women with gestational diabetes

Objective

To evaluate the association between HbA1c levels measured in the third trimester and the risk for large for gestational age (LGA) in neonates of mothers affected by gestational diabetes mellitus (GDM). Secondarily, we aimed to identify an ideal cut-off for increased risk of LGA amongst pregnant women with GDM.

Methods

Observational retrospective review of singleton pregnant women with GDM evaluated in a diabetes and pregnancy clinic of a tertiary and academic hospital. From January/2011 to December/2017, 1,085 pregnant women underwent evaluation due to GDM, of which 665 had an HbA1c test in the third trimester. A logistic regression model was performed to evaluate predictors of LGA. A receiver-operating-characteristic (ROC) curve was used to evaluate the predictive ability of third trimester HbA1c for LGA identification.

Results

A total of 1,085 singleton pregnant women were evaluated during the study period, with a mean age of 32.9 ± 5.3 years. In the multivariate analysis, OGTT at 0 minutes (OR: 1.040; CI 95% 1.006-1.076, p = 0.022) and third trimester HbA1c (OR: 4.680; CI 95% 1.210-18.107, p = 0.025) were associated with LGA newborns. Using a ROC curve to evaluate the predictive ability of third trimester HbA1c for LGA identification, the optimal HbA1c cut-off point was 5.4% where the sensitivity was 77.4% and the specificity was 71.7% (AUC 0.782; p < 0.001).

Conclusion

Few studies in the Mediterranean population have evaluated the role of HbA1c in predicting neonatal complications in women with GDM. A third trimester HbA1c > 5.4% was found to have good sensitivity and specificity for identifying the risk of LGA.

Longitudinal Changes in the Relationship Between Hemoglobin A1c and Glucose Tolerance Across Pregnancy and Postpartum

OBJECTIVE

To characterize the relationship between hemoglobin A1c (HbA1c) levels and glucose tolerance across pregnancy and postpartum.

DESIGN AND PARTICIPANTS

In a longitudinal study of pregnant women with gestational diabetes risk factors (N = 102), we performed oral glucose tolerance testing (OGTT) and HbA1c measurements at 10-15 weeks of gestation, 24-30 weeks of gestation (N = 73), and 6-24 weeks postpartum (N = 42). Complete blood counts were obtained from clinical records. We calculated HbA1c-estimated average glucose levels and compared them with mean OGTT glucose levels (average of fasting, 1- and 2-hour glucose levels). Linear mixed effects models were used to test for longitudinal changes in measurements.

RESULTS

Mean OGTT glucose increased between 10-15 and 24-30 weeks of gestation (β = 8.1 mg/dL, P = .001), while HbA1c decreased during the same time period (β = -0.13%, P < .001). At 10-15 weeks of gestation and postpartum the discrepancy between mean OGTT glucose and HbA1c-estimated average glucose was minimal (mean [standard deviation]: 1.2 [20.5] mg/dL and 0.16 [18.1] mg/dL). At 24-30 weeks of gestation, the discrepancy widened (13.2 [17.9] mg/dL, β = 12.7 mg/dL, P < .001, compared to 10-15 weeks of gestation, with mean OGTT glucose being higher than HbA1c-estimated average glucose). Lower hemoglobin at 24-30 weeks of gestation was associated with a greater discrepancy (β = 6.4 mg/dL per 1 g/dL lower hemoglobin, P = .03 in an age- and gestational age-adjusted linear regression model).

CONCLUSIONS

HbA1c accurately reflects glycemia in the 1st trimester, but underestimates glucose intolerance in the late 2nd trimester. Lower hemoglobin level is associated with greater underestimation. Accounting for gestational age and maternal hemoglobin may improve the clinical interpretation of HbA1c levels during pregnancy.

Intensive Glycemic Treatment During Type 1 Diabetes Pregnancy: A Story of (Mostly) Sweet Success!

Studies from Scotland and Canada confirm large increases in the incidence of pregnancies complicated by pregestational type 1 diabetes (T1D). With this increased antenatal workload comes more specialization and staff expertise, which may be important as diabetes technology use increases. While euglycemia remains elusive and obstetrical intervention (earlier delivery, increased operative deliveries) is increasing, there have been some notable successes in the past 5-10 years. These include a decline in the rates of congenital anomaly (Canada) and stillbirths (U.K.) and substantial reductions in both maternal hypoglycemia (both moderate and severe) across many countries. However, pregnant women with T1D still spend ∼30-45% of the time (8-11 h/day) hyperglycemic during the second and third trimesters. The duration of maternal hyperglycemia appears unchanged in routine clinical care over the past decade. This ongoing fetal exposure to maternal hyperglycemia likely explains the persistent rates of large for gestational age (LGA), neonatal hypoglycemia, and neonatal intensive care unit (NICU) admissions in T1D offspring. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) found that pregnant women using real-time continuous glucose monitoring (CGM) spent 5% less time (1.2 h/day) hyperglycemic during the third trimester, with clinically relevant reductions in LGA, neonatal hypoglycemia, and NICU admissions. This article will review the progress in our understanding of the intensive glycemic treatment of T1D pregnancy, focusing in particular on the recent technological advances in CGM and automated insulin delivery. It suggests that even with advanced diabetes technology, optimal maternal dietary intake is needed to minimize the neonatal complications attributed to postprandial hyperglycemia.

Translating HbA1c measurements into estimated average glucose values in pregnant women with diabetes

AIMS/HYPOTHESIS

This study aimed to examine the relationship between average glucose levels, assessed by continuous glucose monitoring (CGM), and HbA_1c levels in pregnant women with diabetes to determine whether calculations of standard estimated average glucose (eAG) levels from HbA_1c measurements are applicable to pregnant women with diabetes.

METHODS

CGM data from 117 pregnant women (89 women with type 1 diabetes; 28 women with type 2 diabetes) were analysed. Average glucose levels were calculated from 5-7 day CGM profiles (mean 1275 glucose values per profile) and paired with a corresponding (±1 week) HbA_1c measure. In total, 688 average glucose-HbA_1c pairs were obtained across pregnancy (mean six pairs per participant). Average glucose level was used as the dependent variable in a regression model. Covariates were gestational week, study centre and HbA_1c.

RESULTS

There was a strong association between HbA_1c and average glucose values in pregnancy (coefficient 0.67 [95% CI 0.57, 0.78]), i.e. a 1% (11 mmol/mol) difference in HbA_1c corresponded to a 0.67 mmol/l difference in average glucose. The random effects model that included gestational week as a curvilinear (quadratic) covariate fitted best, allowing calculation of a pregnancy-specific eAG (PeAG). This showed that an HbA_1c of 8.0% (64 mmol/mol) gave a PeAG of 7.4-7.7 mmol/l (depending on gestational week), compared with a standard eAG of 10.2 mmol/l. The PeAG associated with maintaining an HbA_1c level of 6.0% (42 mmol/mol) during pregnancy was between 6.4 and 6.7 mmol/l, depending on gestational week.

CONCLUSIONS/INTERPRETATION

The HbA_1c-average glucose relationship is altered by pregnancy. Routinely generated standard eAG values do not account for this difference between pregnant and non-pregnant individuals and, thus, should not be used during pregnancy. Instead, the PeAG values deduced in the current study are recommended for antenatal clinical care.

Rational use of electronic health records for diabetes population management

Population management is increasingly invoked as an approach to improve the quality and value of diabetes care. Recent emphasis is driven by increased focus on both costs and measures of care as the US moves from fee for service to payment models in which providers are responsible for costs incurred, and outcomes achieved, for their entire patient population. The capacity of electronic health records (EHRs) to create patient registries, apply analytic tools, and facilitate provider- and patient-level interventions has allowed rapid evolution in the scope of population management initiatives. However, findings on the efficacy of these efforts for diabetes are mixed, and work remains to achieve the full potential of an-EHR based population approach. Here we seek to clarify definitions and key domains, provide an overview of evidence for EHR-based diabetes population management, and recommend future directions for applying the considerable power of EHRs to diabetes care and prevention.

Innovative uses of electronic health records and social media for public health surveillance

Electronic health records (EHRs) and social media have the potential to enrich public health surveillance of diabetes. Clinical and patient-facing data sources for diabetes surveillance are needed given its profound public health impact, opportunity for primary and secondary prevention, persistent disparities, and requirement for self-management. Initiatives to employ data from EHRs and social media for diabetes surveillance are in their infancy. With their transformative potential come practical limitations and ethical considerations. We explore applications of EHR and social media for diabetes surveillance, limitations to approaches, and steps for moving forward in this partnership between patients, health systems, and public health.

Body weight, weight gain and hyperglycaemia are associated with hypertensive disorders of pregnancy in women with gestational diabetes

AIM

The aim of this study was to measure the capacity of glucose- and weight-related parameters to predict pregnancy-induced hypertensive disorders in women with gestational diabetes.

METHODS

An observational study was conducted involving 2037 women with gestational diabetes. The associations of glycaemic and weight-related parameters with pregnancy-induced hypertensive disorders were obtained by univariate and adjusted multivariate analyses. Also, model predictability and attributable predictor risk percentages were calculated, and collinearity and factor interactions examined.

RESULTS

Multivariate analyses revealed that hypertensive disorders were mainly predicted by average third-trimester glycated haemoglobin (HbA(1c)) levels ≥ 5.9%, by being overweight or obese before pregnancy and by excess gestational weight gain after adjusting for age, tobacco use, chronic hypertension, parity, urinary tract infections and gestational age at delivery. Prepregnancy body weight (overweight and obesity) had the strongest impact on pregnancy-related hypertensive disorders (attributable risk percentages were 51.5% and 88.8%, respectively). The effect of being overweight or obese on hypertensive disorders was enhanced by HbA(1c) levels and gestational weight gain, with elevated HbA(1c) levels multiplying the effect of being overweight before pregnancy.

CONCLUSION

The average third-trimester HbA1c level is a novel risk factor for pregnancy-induced hypertensive disorders in women with gestational diabetes. HbA(1c) levels ≥ 5.9%, prepregnancy overweight or obesity and excess gestational weight gain are all independent risk factors of pregnancy-related hypertensive disorders in such women. In treated gestational diabetes patients, the strongest influence on hypertensive disorders is prepregnancy obesity.

The association between sex hormone-binding globulin and type 2 diabetes in Nigerian men

Background

Epidemiological studies have shown that sex hormone-binding globulin (SHBG) has a role in glucose homeostasis in both men and women. However, a prospective study on Japanese-American subjects concluded that SHBG was not a significant risk factor in either men or women, suggesting ethnic differences. We were not aware of any evaluation of SHBG in subjects of African ancestry.

Objectives

We investigated the association between SHBG and insulin resistance in type 2 diabetic diabetic men in a hospital in Nigeria.

Method

Forty-eight male subjects with type 2 diabetes and 20 non-diabetic male subjects were recruited in this cross-sectional hospital-based study by the convenient sampling method. Height and circumferences around the waist and hip were measured to the nearest 0.5 cm and the waist–hip ratio was calculated from this measurement. Weight was measured and body mass index was calculated. Fasting plasma glucose concentration was measured by the glucose oxidase method with a between-run coefficient of variation of 3%. Insulin and SHBG were measured by means of enzyme-linked immunosorbent assay (ELISA).

Results

There was a statistically-significant difference between test results for the diabetic and non-diabetic patients. The mean SHBG concentration was higher in the non-diabetic group (42.2 nmol/L) than the diabetic group (30.5 nmol/L). A significant inverse association between insulin resistance and SHBG was observed (r = 0.353, p < 0.015).

Conclusion

This study supported earlier observations that a significant inverse correlation exists between SHBG and insulin resistance and provides evidence that the relationship may extend to type 2 diabetic men of African ancestry in Nigeria.

Enhanced absorption of insulin aspart as the result of a dispersed injection strategy tested in a randomized trial in type 1 diabetic patients

OBJECTIVE

We investigated the impact of two different injection strategies on the pharmacokinetics and pharmacodynamics of insulin aspart in vivo in an open-label, two-period crossover study and verified changes in the surface-to-volume ratio ex vivo.

RESEARCH DESIGN AND METHODS

Before the clinical trial, insulin aspart was injected ex vivo into explanted human abdominal skin flaps. The surface-to-volume ratio of the subcutaneous insulin depot was assessed by microfocus computed tomography that compared 1 bolus of 18 IU with 9 dispersed boluses of 2 IU. These two injection strategies were then tested in vivo, in 12 C-peptide-negative type 1 diabetic patients in a euglycemic glucose clamp (glucose target 5.5 ± 1.1 mmol/L) for 8 h after the first insulin administration.

RESULTS

The ex vivo experiment showed a 1.8-fold higher mean surface-to-volume ratio for the dispersed injection strategy. The maximum glucose infusion rates (GIR) were similar for the two strategies (10 ± 4 vs. 9 ± 4; P = 0.5); however, times to reach maximum GIR and 50% and 10% of the maximum GIR were significantly reduced by using the 9 × 2 IU strategy (68 ± 33 vs. 127 ± 93 min; P = 0.01; 38 ± 9 vs. 49 ± 16 min; P < 0.01; 23 ± 6 vs. 30 ± 10 min; P < 0.05). For 9 × 2 IU, the area under the GIR curve was greater during the first 60 min (219 ± 89 vs. 137 ± 75; P < 0.01) and halved until maximum GIR (242 ± 183 vs. 501 ± 396; P < 0.01); however, it was similar across the whole study period (1,361 ± 469 vs. 1,565 ± 527; P = 0.08).

CONCLUSIONS

A dispersed insulin injection strategy enhanced the effect of a fast-acting insulin analog. The increased surface-to-volume ratio of the subcutaneous insulin depot can facilitate insulin absorption into the vascular system.

The metabolic deterioration that antedates diabetes: personal trajectories of HbA(1c) and fasting glucose as early indicators and possible triggers for intervention

HbA(1c) testing has become an accepted means of diagnosing diabetes as an alternative to blood glucose levels. However, population-based norms of glucose and of HbA(1c) levels do not enable the detection of diabetes at an early enough stage to thwart complications. Personal trajectories of glucose levels show steep increases a number of years prior to diabetes diagnosis. Here, we hypothesize that a comparable time-dependent deviation in an individual's HbA(1c) level may be an early manifestation of disease that should prompt lifestyle modifications. We predict that analysis of personal trajectories of glucose and of HbA(1c) will promote earlier intervention and a greater reduction in disease complications than current standards, which are based on population-based norms.

Antenatal haemoglobin A1c and risk of large-for-gestational-age infants in a multi-ethnic cohort of women with gestational diabetes

Gestational diabetes mellitus (GDM) is a risk factor for delivering a large-for-gestational-age (LGA) infant. Haemoglobin A1c (A1C) is an indicator of glycaemic control. The objective of this study was to test whether higher A1C quartile at the time of diagnosis of GDM is associated with increased risk of delivering a LGA or macrosomic infant. Women with singleton pregnancies treated for GDM at a large diabetes and pregnancy programme located in Charlotte, North Carolina, were eligible for inclusion in this retrospective cohort study. Clinical information, including A1C at diagnosis, treatment, prior medical and obstetric history, and birth data were abstracted from medical records. LGA was defined as birthweight >90th percentile for gestational age and sex and macrosomia as birthweight >4000 g. Logistic regression was used to analyse the association of A1C at GDM diagnosis with risk of delivering LGA or macrosomic infants. This study included 502 women. Prevalences of LGA and macrosomia were 4% and 6% respectively. After adjustment there was no detectable trend of increased risk for LGA (P for trend = 0.12) or macrosomia (P for trend = 0.20) across increasing quartiles of A1C at GDM diagnosis. A1C at GDM diagnosis may not be linearly associated with LGA or macrosomia, possibly because of the mediating effect of strict glycaemic control in this clinical setting.

Hemoglobin A1c and postpartum abnormal glucose tolerance among women with gestational diabetes mellitus

OBJECTIVE

To analyze the association of hemoglobin A1c (HbA1c) at gestational diabetes mellitus (GDM) diagnosis with postpartum abnormal glucose in a cohort of women with GDM.

METHODS

Women with singleton pregnancies treated for GDM at a large diabetes and pregnancy program located in Charlotte, North Carolina, who completed a postpartum 2-hour oral glucose tolerance test were eligible for inclusion in this retrospective cohort study. Clinical information, including maternal HbA1c at diagnosis, was abstracted from medical records. A parametric survival model was used to assess the association of HbA1c at GDM diagnosis with postpartum maternal abnormal glucose including impaired fasting glucose, impaired glucose tolerance, and any postpartum abnormal glucose.

RESULTS

Of the 277 postpartum women with GDM, 75 (32%) had impaired fasting glucose, 61 (28%) had impaired glucose tolerance, and 15 (9%) were diagnosed with type 2 diabetes mellitus after delivery. After adjustment for clinic, maternal age, parity, prepregnancy body mass index 25 or higher, nonwhite race or ethnicity, and gestational week at first HbA1c, we detected a trend of increased risk for impaired fasting glucose (P=.01), impaired glucose tolerance (P=.002), and any glucose abnormality (P<.001) associated with increased quartile of HbA1c at GDM diagnosis.

CONCLUSION

Hemoglobin A1c measured at GDM diagnosis may be a useful tool for identifying patients with GDM at highest risk of developing postpartum abnormal glucose.

Is there a relationship between mean blood glucose and glycated hemoglobin?

Measurement of hemoglobin A1c (HbA1c) is considered the gold standard for monitoring chronic glycemia of diabetes patients. Hemoglobin A1c indicates an average of blood glucose levels over the past 3 months. Its close association with the risk for the development of long-term complications is well established. However, HbA1c does not inform patients about blood glucose values on a daily basis; therefore, frequent measurements of blood glucose levels are necessary for the day-to-day management of diabetes. Clinicians understand what HbA1c means and how it relates to glucose, but this is not the case with patients. Therefore, the translation of the HbA1c results into something more familiar to patients seemed a necessity. The scope of this article is to review the literature to search for enough scientific evidence to support the idea of a close relationship between HbA1c and mean blood glucose (MBG), and to justify the translation of HbA1c into something that reflects the MBG. Most studies confirm a close relationship between HbA1c and MBG, although different studies result in different linear equations. Factors affecting this relationship may limit the usefulness and applicability of a unique mathematical equation to all diabetes populations.

Use of insulin lispro during pregnancy in women with pregestational diabetes mellitus

BACKGROUND AND OBJECTIVE

To assess the safety and efficacy of insulin analogues versus human insulin in pregnant women with pregestational diabetes.

PATIENTS AND METHODS

We collected data on pregnant women with type 1 or type 2 diabetes who were attended at the Diabetes and Pregnancy Unit between January 1998 and April 2008 (N=351). Two hundred and forty one patients were treated with regular insulin and NPH and 110 were treated with different combinations of insulins including an insulin analogue (most of them with NPH and lispro).

RESULTS

There was no significant difference in terms of congenital malformation rate between groups (3.3% and 3.6%). The group on insulin analogue had slightly higher mean HbA1c during the first trimester than the group on human insulin (6.6 [1.0]% vs 6.9 [1.1]%; P=0,022) and needed smaller insulin doses during whole pregnancy. Severe hypoglycaemia was significantly less frequent among women treated with a rapid insulin analogue (2.3 vs 10.0%; P=0,025). Neonatal hypoglycaemia was significantly more frequent in the group treated with a rapid insulin analogue (34.9 vs 23.6%; P=0.043) due to the concomitant use of an insulin pump. Other obstetric and neonatal variables were not different between the two groups.

CONCLUSION

Our study shows that insulin analogues are safe during pregnancy in women with pregestational diabetes mellitus. Overall, glycaemic control, maternal and foetal outcome were similar to those with human insulin. The main advantage with respect to human insulin was to importantly reduce maternal severe hypoglycaemia.

Glycated hemoglobin (HbA1c): old dogmas, a new perspective?

The hemoglobin A1c (HbA1c) assay provides a reliable measure of chronic glycemia and correlates well with the risk of long-term diabetes complications, so that it is currently considered the test of choice for monitoring and chronic management of diabetes. Recently, HbA1c testing has been included within the diagnostic criteria recommended for diagnosis of diabetes in nonpregnant individuals by the American Diabetes Association (ADA). The emerging concept that HbA1c can be used rather than blood glucose in the diagnosis of diabetes is highly appealing for a variety of reasons, including less sensitivity to preanalytical variables, lower within subject biological variability, little to null interference from diurnal variations, acute stress and common drugs which are known to influence glucose metabolism, as well as the fact that one single measurement might provide information for both diagnosing diabetes and tracking glycemic control. On the other hand, the use of HbA1c for screening and diagnosing diabetes also carries some limitations, including the worse diagnostic performance in different populations (i.e., pregnancy, elderly and non-Hispanic blacks), the risk of overdiagnosis in subjects with iron deficiency anemia, in subjects genetically predisposed to hyperglycation, and in those with increased red blood cell turnover. There is also a higher risk of misdiagnosis in patients with end-stage renal disease and heavy alcohol consumption. Finally, HbA1c testing might be biased due to the interference from several hemoglobin variants, is characterized by a higher imprecision than blood glucose measurement, and is more expensive. This paper will critically summarize the potential advantages and limitations of HbA1c as a recommended test for diagnosing diabetes.

The proposed terminology 'A(1c)-derived average glucose' is inherently imprecise and should not be adopted

The proposed use of a more precise standard for glycated (A(1c)) and non-glycated haemoglobin would lead to an A(1c) value, when expressed as a percentage, that is lower than that currently in use. One approach advocated to address the potential confusion that would ensue is to replace 'HbA(1c)' with a new term, 'A(1c)-derived average glucose.' We review evidence from several sources suggesting that A(1c) is, in fact, inherently imprecise as a measure of average glucose, so that the proposed terminology should not be adopted.