Comparison of HbA1c and OGTT for the diagnosis of type 2 diabetes in children at risk of diabetes

Characteristics of Children and Adolescents with Hyperinsulinemia Undergoing Oral Glucose Tolerance Test: A Single-Center Retrospective Observational Study

The aim of this study was to evaluate a potential correlation between results of the oral glucose tolerance test (OGTT) and the auxological/metabolic parameters in a cohort of overweight patients assessed for suspicion of hyperinsulinism. We analyzed 206 patients, comparing those with insulin peak below (nonhyperinsulinemic) and over 100 uIU/mL (hyperinsulinemic) at the OGTT. We found a significant difference in weight (p = 0.037), body mass index (BMI, p < 0.001) and BMI standard deviations (SD, p < 0.001), waist circumference (p = 0.001), hip circumference (p = 0.001), and waist-to-height ratio (WHtR, p = 0.016) between the two groups. Analyzing the median insulin value during OGTT in the whole population, a weakly positive correlation emerged with weight SD (p < 0.001; rho = 0.292) and a moderate positive correlation with BMI SD (p < 0.001; rho = 0.323). We also found a weakly positive correlation with waist circumference (p = 0.001; rho = 0.214), hip circumference (p = 0.001; rho = 0.217), and WHTR (p = 0.016; rho = 0.209) and a moderate positive correlation with the HOMA index (p < 0.001; rho = 0.683). The median insulin value correlates with high triglyceride (p < 0.001; rho = 0.266) and triiodothyronine values (p = 0.003; rho = 0.193) and with low HDL values (p < 0.001; rho = -0.272). In clinical practice the interpretation of laboratory and anthropometric parameters could predict the level of insulin, highlighting also a possible underlying diagnosis of insulin resistance and/or hyperinsulinemia without performing an OGTT.

The clinical significance of serum HbA1c to diagnose diabetes mellitus during acute pancreatitis

AIMS

To investigate the prevalence of diabetes mellitus (DM) in acute pancreatitis (AP) patients and to explore the extent to which inflammatory stress affects plasma glucose (PG) levels in AP patients.

METHODS

A retrospective analysis of 2163 AP patients was performed. The PG differences among AP patients under differing pancreatic necrosis conditions and inflammation severity were compared. Receiver operating characteristic curves were used to assess whether fasting PG in the inflammatory stage of AP might be used for DM screening.

RESULTS

The overall DM prevalence was 19.97% in AP patients, 32.41% of whom had newly diagnosed DM (based on HbA1c levels in patients who self-reported no DM). The DM prevalence was 46.93% in hyperlipidemic AP patients, 44.14% of whom had newly diagnosed DM. In patients with and without pancreatic necrosis, the optimal PG thresholds for the screening of newly diagnosed DM were 10.40 mmol/L and 8.21 mmol/L, respectively, with an AUC of 0.959 ± 0.034 (P < 0.001) and 0.972 ± 0.006 (P < 0.001), respectively.

CONCLUSIONS

For hospitalized AP patients and fasting PG levels exceeding 10 mmol/L (with necrosis) or 8 mmol/L (without necrosis) (P < 0.001), HbA1c testing is recommended to investigate the presence of comorbid undiagnosed DM.

Are glucose and insulin levels at all time points during OGTT a reliable marker of diabetes mellitus risk in pediatric obesity?

PURPOSE

Childhood overweight and obesity associated with insulin resistance and metabolic syndrome represent the new global pandemic and the main causative factors for dysglycemia, prediabetes, and Type 2 Diabetes Mellitus (T2DM). Predictors, such as HOMA-IR, HOMA-β%, and QUICKI lack specific reference values in children. OGTT is a gold standard for glycometabolic assessment. Recently, a glycemic level higher than 155 mg/dl at + 60' after glucose ingestion has been defined as a risk factor for T2DM in obese adolescents. We aim to analyze and correlate fasting insulin-resistance markers with OGTT results in overweight/obese children and adolescents.

METHODS

We retrospectively evaluated glucose and insulin values during a 2-h OGTT every 30 min in 236 overweight/obese patients. Glucose values and insulin sum during OGTT were compared to glycometabolic indexes and different cut-off values for insulin sum.

RESULTS

A 1-h glucose > 155 mg/dl and insulin sum > 535 microU/ml at all times during OGTT are the best predictors of diabetes risk in obese youths. A1-h glucose > 155 mg/dl is significantly associated with HbA1c > 5.7%, while no association was observed between HbA1c > 5.7% and glucose levels at baseline and 2 h. The ability of the standardized HOMA-IR to predict the prediabetes status is clearly lower than the total insulin sum at OGTT.

CONCLUSION

Our study demonstrates that also 1-h post-OGTT glucose, together with HbA1c, is an effective diabetes predictor.

Evaluation of the hemoglobin a1c test in detecting pediatric prediabetes

Aim: The aim of this study is to evaluate the diagnostic performance of the hemoglobin a1c (Hba1c) test in pediatric prediabetes, and to determine the cut-off value for the pediatric age , to examine the relationship of the Hba1c test between glucose levels,. Materials and Methods: This study was carried out by retrospectively evaluating the data of 548 children. Prediabetes cases were determined by taking fasting and oral glucose tolerance test (OGTT) 2 hour (2h) glucose levels as a reference. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for Hba1c, fasting, and OGTT 2h glucose tests. The area under the curve (AUC) was calculated for each test by receiver-operating characteristic analysis. Results: Based on glucose values, 1.6% of individuals were assigned to the diabetes mellitus, 14.6% to prediabetes, and 83.8% to normoglycemia group. When 5.7 was used as the threshold value for Hba1c in prediabetes, the sensitivity was 31.3%, specificity was 87.8%, PPV was 30.9%, and NPV was 88.0%, AUC:0,686. The optimal cut-off value of Hba1c was determined as 5.35%. At this value, the sensitivity was calculated as 66.3% and the specificity as 61.4%. Conclusion: Although the use of adult HbA1c criteria for the diagnosis of prediabetes in the pediatric ages is controversial due to the differences between the results of OGTT and HbA1c-based tests, prediabetes screening is still important. HbA1c≥5.35 will be useful to follow up on children with prediabetes in terms of risk and to screen them with OGTT.

Natural history and determinants of dysglycemia in Canadian children with parental obesity from ages 8-10 to 15-17 years: The QUALITY cohort

In children, the mechanisms implicated in deterioration of glucose homeostasis versus reversion to normal glucose tolerance (NGT) remain uncertain. We aimed to describe the natural history of dysglycemia from childhood to late adolescence and to identify its early determinants. We used baseline (8-10 years, n = 630), 1st follow-up (10-12 years, n = 564) and 2nd follow-up (15-17 years, n = 377) data from the QUALITY cohort of White Canadian children with parental obesity. Children underwent a 2-h oral glucose tolerance test at each cycle with plasma glucose and insulin measured at 0/30/60/90/120 min. American Diabetes Association criteria defined dysglycemia (impaired fasting glucose, impaired glucose tolerance or type 2 diabetes). Longitudinal patterns of insulin sensitivity and beta-cell function were estimated using generalized additive mixed models. Model averaging identified biological, sociodemographic and lifestyle-related determinants of dysglycemia. Of the children NGT at baseline, 66 (21%) developed dysglycemia without reverting to NGT. Among children with dysglycemia at baseline, 24 (73%) reverted to NGT. In children with dysglycemia at 1st follow-up, 18 (53%) later reverted to NGT. Among biological, sociodemographic and lifestyle determinants at 8-10 years, only fasting and 2-h glucose were associated with developing dysglycemia (odds ratio [95% CI] per 1 mmol/L increase: 4.50 [1.06; 19.02] and 1.74 [1.11; 2.73], respectively). Beta-cell function decreased by 40% in children with overweight or obesity. In conclusion, up to 75% of children with dysglycemia reverted to NGT during puberty. Children with higher fasting and 2-h glucose were at higher risk for progression to dysglycemia, while no demographic/lifestyle determinants were identified.

Review of methods for detecting glycemic disorders

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.