Oral glucose tolerance test-based calculation identifies different glucose intolerance phenotypes within the impaired fasting glucose range

Prediction of type 2 diabetes mellitus using fasting plasma glucose and HbA1c levels among individuals with impaired fasting plasma glucose: a cross-sectional study in Thailand

OBJECTIVES

About 11%-30% of individuals with impaired fasting plasma glucose (IFG) have type 2 diabetes mellitus (T2DM), diagnosed by the 75 g oral glucose tolerance test (75 g OGTT). This study investigated (1) the prevalence and cut-off levels for fasting plasma glucose (FPG) and glycated haemoglobin A1c (HbA1c) in IFG individuals that most effectively predict the presence of T2DM diagnosed by a 75 g OGTT; (2) the predictors associated with T2DM; and (3) the pathophysiological characteristics of patients with IFG.

MATERIALS AND METHODS

A single-centre, cross-sectional study was conducted in a primary care setting. A standard 75 g OGTT was performed on 123 subjects with IFG. Their beta-cell function and insulin resistance were calculated through plasma glucose and insulin levels monitored during the 75 g OGTT.

RESULTS

In the IFG subjects, the prevalence of T2DM using the 2-hour postload plasma glucose (2hPG) criterion was 28.5%. Pre-diabetes and normal glucose metabolism were found in 48.7% and 22.8%, respectively, by 75 g OGTT. An HbA1c level ≥6.0% or FPG ≥5.9 mmol/L were the optimal cut-off thresholds for the prediction of the presence of T2DM. HbA1c had a sensitivity of 76.7% and specificity of 55.7% (95% CI 57.7% to 90.1% and 95% CI 43.3% to 67.6%, respectively), while FPG had a sensitivity of 85.7% and specificity of 23.9% (95% CI 69.7% to 95.2% and 95% CI 15.4% to 34.1%, respectively). The presence of metabolic syndrome, a higher HbA1c and higher FPG levels were associated with the risk of T2DM in the Thai IFG population.

CONCLUSIONS

Almost one-third of the people with IFG had T2DM diagnosed by the 2hPG criterion. HbA1c was more effective than FPG in predicting the presence of T2DM in the IFG subjects. IFG individuals with HbA1c≥6.0% or FPG≥5.9 mmol/L should be advised to undergo a 75 g OGTT to detect T2DM earlier than otherwise.

Oral glucose tolerance test-based calculation identifies different glucose intolerance phenotypes within the impaired fasting glucose range

Aims/Introduction

The conventional oral glucose tolerance test (OGTT) cannot detect future diabetics among isolated impaired fasting glucose (is‐IFG) nor normal glucose tolerant (NGT) groups. By analyzing the relationship between fasting (FPG) and 2‐h plasma glucose (2hPG), the present study identifies is‐IFG subjects liable to worsening glucose homeostasis.

Materials and Methods

Oral glucose tolerance test was carried out in 619 patients suffering from obesity, hypertension or dyslipidemia, whose FPG was in the 100–125 mg/dL range. We calculated the percentage increment of 2hPG with respect to FPG (PG%) in these patients using the formula: ([2hPG − FPG] / FPG) × 100. Differences in β‐cell function within is‐IFG patients were assessed by estimated insulin sensitivity index (EISI), first‐phase insulin release (1stPH) and 1stPH/1/EISI (1stPH_corrected).

Results

Diabetes was diagnosed in 69 patients (11.2%), combined IFG/impaired glucose tolerance (IGT) in 185 patients (29.9%) and is‐IFG in 365 patients (58.9%). Is‐IFG was subdivided into PG% tertile groups: the percentage of females increased from 25% in the lowest to 45.2% in the highest tertile (χ² = 18.7, P < 0.001). Moving from the lowest to the highest PG% tertile group, insulin and 2hPG concentrations rose, whereas FPG, EISI, and 1stPH_corrected decreased progressively and significantly. Furthemore, PG% correlated inversely with EISI (r = −0.44, P < 0.0001) and 1stPH_corrected (r = −0.38, P < 0.0001).

Conclusions

Oral glucose tolerance test does differentiate the great heterogeneity in metabolic disorders of patients with FPG 100–125 mg/dL. Furthermore, PG% can expand the diagnostic power of OGTT in the is‐IFG range by distinguishing metabolic phenotypes very likely to herald different clinical risks.