Glycemic control indicators in patients with neonatal diabetes mellitus

Correlation between hyperglycemia and glycated albumin with retinopathy of prematurity

To determine the association between hyperglycemia, glycated albumin (GlyA) and retinopathy of prematurity (ROP). Prospective study of all infants under ROP screening from March 2017 to July 2019. All demographic, clinical and laboratory data were collected. Glucose was measured at birth and every 8 h for the first week and serum GlyA was evaluated at birth, 1st, 2nd and 4th weeks after birth. Reference range for GlyA was obtained. Univariate logistic regression was used to examine risk factors for ROP followed by multivariate regression. A total of 152 infants were included in the study. Median gestational age was 30 weeks and median birth weight 1240 g. Thirty-three infants (21.7%) had ROP. Hyperglycemia was present in 24 (72.7%) infants diagnosed with any ROP versus 6 (0.05%) in those without ROP. Median GlyA at birth, 1st, 2nd and 4th and respective reference ranges were 8.50% (6.00-12.65), 8.20% (5.32-11.67), 8.00% (5.32-10.00) and 7.90% (5.30-9.00) respectively. After multivariate logistic regression, hyperglycemia but not GlyA, remained a significant risk factor for ROP overpowering the other recognized risk factors (Exp (B) 28.062, 95% CI for Exp(B) 7.881-99.924 p < 0.001). In our cohort, hyperglycemia but not GlyA, remained a significant risk factor for ROP overpowering the other recognized risk factors.

Feasibility of neonatal haemoglobin A1C as a biomarker for retinopathy of prematurity

INTRODUCTION

Retinopathy of prematurity (ROP) is a potentially serious eye disorder affecting very preterm infants. Non-proliferative ROP (NP-ROP), also known as Early Stage ROP, is characterized by deficient retinal angiogenesis. Proliferative ROP (P-ROP), also known as Late Stage ROP, is characterized by pathologic angiogenesis. The use of neonatal haemoglobin A1C as a biomarker for ROP has not yet been evaluated.

MATERIALS AND METHODS

We modified the Haemoglobin A1C assay for use with neonatal dried blood spots (DBS) and then assessed A1C levels via Elisa immunoassay on DBS from 43 preterm infants (with gestational ages 26-28 weeks). We measured A1C on DBS collected at <1 week and 4 weeks of chronological age.

RESULTS

Compared to matched counterparts without ROP, there is significantly lower HbA1c in infants who develop NP-ROP, this occurs at Week 4 (p=0.004), but is not seen at Week 1; there is significantly higher HbA1c in infants with P-ROP, this occurs both at Week 1 (p<0.05) and Week 4 (p=0.005).

CONCLUSIONS

The A1C test, modified for use with DBS, is a feasible biomarker for ROP; low A1C is a potential biomarker for non-proliferative ROP and high A1C is for proliferative ROP.

Neonatal diabetes mellitus due to a novel variant in the INS gene

Neonatal diabetes mellitus (NDM) is a rare condition that presents with diabetes in the first few months of life. The treatment of NDM may differ depending on the genetic etiology, with numerous studies showing the benefit of sulfonylurea therapy in cases caused by mutations in KCNJ11 or ABCC8 Mutations in the insulin gene (INS) have also been identified as causes of NDM; these cases are generally best treated with insulin alone. We report a case of a female infant born small for gestational age (SGA) at late preterm diagnosed with NDM at 7 wk of life who was found by rapid whole-genome sequencing to harbor a novel de novo c.26C>G (p.Pro9Arg) variant in the INS gene. She presented with diabetic ketoacidosis, which responded to insulin therapy. She did not respond to empiric trial of sulfonylurea therapy early in her hospital course, and it was discontinued once a genetic diagnosis was made. Early genetic evaluation in patients presenting with NDM is essential to optimize therapeutic decision-making.

A Comparison of Biomarkers in the Assessment of Glycemic Control in Diabetes: Reviewing the Evidence

BACKGROUND

Diabetes Mellitus (DM) is a chronic life-long progressive multisystem heterogeneous metabolic disorder with complex pathogenesis.

INTRODUCTION

Hyperglycemia is not only one of the classical signs of DM, but it also serves as the pivotal prerequisite for the diagnosis of the disease. However, with the advancement in the field of analytical biochemistry, a number of alternative and specific biomarkers have been discovered which can be used for better diagnosis of the DM. In this review, we have discussed various aspects of DM and different biomarkers used in assessing glycemia.

METHODOLOGY

A thorough literature survey was conducted to identify various studies that reported the use of conventional and non-conventional markers for the assessment of glycemia in DM patients.

CONCLUSION

The accurate detection and hence diagnosis of DM has become easy and more specific with the use of various biomarkers.

Glycemic control indicator levels at diagnosis of neonatal diabetes mellitus: Comparison with other types of insulin-dependent diabetes mellitus

BACKGROUND

Neonatal diabetes mellitus (NDM) is a monogenic insulin-dependent diabetes that develops within 6 months of age. The progression of hyperglycemia until diagnosis is unknown. Glycemic control indicators at diagnosis are useful to estimate the extent and duration of hyperglycemia. We recently established that age-adjusted glycated albumin (GA) is a useful indicator of glycemic control, regardless of age.

OBJECTIVE

To compare the levels of various glycemic control indicators at diagnosis between NDM and other types of insulin-dependent diabetes mellitus.

PATIENTS AND METHODS

We included 8 patients with NDM, 8 with fulminant type 1 diabetes (FT1D), and 24 with acute-onset autoimmune type 1 diabetes (T1AD). Plasma glucose, glycated hemoglobin (HbA1c), GA, and age-adjusted GA (calculated as previously reported) were measured and compared.

RESULTS

There were no significant differences in the plasma glucose levels of the group of patients with NDM and those with FT1D or T1AD. HbA1c and GA levels in the NDM group were not significantly different from those in the FT1D group, and both indicators were lower than those in the T1AD group. Age-adjusted GA levels in the NDM group did not differ significantly from those in the T1AD group, but were higher than those in the FT1D group.

CONCLUSIONS

These findings suggest that the time-course of plasma glucose elevation in NDM until diagnosis is similar to that in T1AD. In addition, the high age-adjusted GA value at diagnosis of NDM indicates that this test is useful for assessing chronic hyperglycemia in NDM.

Effects of a Follow-On Formula Containing Isomaltulose (Palatinose™) on Metabolic Response, Acceptance, Tolerance and Safety in Infants: A Randomized-Controlled Trial

Effects of the dietary glycaemic load on postprandial blood glucose and insulin response might be of importance for fat deposition and risk of obesity. We aimed to investigate the metabolic effects, acceptance and tolerance of a follow-on formula containing the low glycaemic and low insulinaemic carbohydrate isomaltulose replacing high glycaemic maltodextrin. Healthy term infants aged 4 to 8 completed months (n = 50) were randomized to receive the intervention follow-on formula (IF, 2.1g isomaltulose (Palatinose™)/100mL) or an isocaloric conventional formula (CF) providing 2.1g maltodextrin/100mL for four weeks. Plasma insulinaemia 60min after start of feeding (primary outcome) was not statistically different, while glycaemia adjusted for age and time for drinking/volume of meal 60min after start of feeding was 122(105,140) mg/dL in IF (median, interquartile range) and 111(100,123) in CF (p = 0.01). Urinary c-peptide:creatinine ratio did not differ (IF:81.5(44.7, 96.0) vs. CF:56.8(37.5, 129),p = 0.43). Urinary c-peptide:creatinine ratio was correlated total intake of energy (R = 0.31,p = 0.045), protein (R = 0.42,p = 0.006) and fat (R = 0.40,p = 0.01) but not with carbohydrate intake (R = 0.22,p = 0.16). Both formulae were well accepted without differences in time of crying, flatulence, stool characteristics and the occurrence of adverse events. The expected lower postprandial plasma insulin and blood glucose level due to replacement of high glycaemic maltodextrin by low glycaemic isomaltulose were not observed in the single time-point blood analysis. In infants aged 4 to 8 completed months fed a liquid formula, peak blood glucose might be reached earlier than 60min after start of feeding. Non-invasive urinary c-peptide measurements may be a suitable marker of nutritional intake during the previous four days in infants.

Trial registration: ClinicalTrials.gov NCT01627015

Utility of different glycemic control metrics for optimizing management of diabetes

The benchmark for assessing quality of long-term glycemic control and adjustment of therapy is currently glycated hemoglobin (HbA1c). Despite its importance as an indicator for the development of diabetic complications, recent studies have revealed that this metric has some limitations; it conveys a rather complex message, which has to be taken into consideration for diabetes screening and treatment. On the basis of recent clinical trials, the relationship between HbA1c and cardiovascular outcomes in long-standing diabetes has been called into question. It becomes obvious that other surrogate and biomarkers are needed to better predict cardiovascular diabetes complications and assess efficiency of therapy. Glycated albumin, fructosamin, and 1,5-anhydroglucitol have received growing interest as alternative markers of glycemic control. In addition to measures of hyperglycemia, advanced glucose monitoring methods became available. An indispensible adjunct to HbA1c in routine diabetes care is self-monitoring of blood glucose. This monitoring method is now widely used, as it provides immediate feedback to patients on short-term changes, involving fasting, preprandial, and postprandial glucose levels. Beyond the traditional metrics, glycemic variability has been identified as a predictor of hypoglycemia, and it might also be implicated in the pathogenesis of vascular diabetes complications. Assessment of glycemic variability is thus important, but exact quantification requires frequently sampled glucose measurements. In order to optimize diabetes treatment, there is a need for both key metrics of glycemic control on a day-to-day basis and for more advanced, user-friendly monitoring methods. In addition to traditional discontinuous glucose testing, continuous glucose sensing has become a useful tool to reveal insufficient glycemic management. This new technology is particularly effective in patients with complicated diabetes and provides the opportunity to characterize glucose dynamics. Several continuous glucose monitoring (CGM) systems, which have shown usefulness in clinical practice, are presently on the market. They can broadly be divided into systems providing retrospective or real-time information on glucose patterns. The widespread clinical application of CGM is still hampered by the lack of generally accepted measures for assessment of glucose profiles and standardized reporting of glucose data. In this article, we will discuss advantages and limitations of various metrics for glycemic control as well as possibilities for evaluation of glucose data with the special focus on glycemic variability and application of CGM to improve individual diabetes management.