BMJ Open Diabetes Research & Care最新文献

Introduction: Women with a history of gestational diabetes mellitus (GDM) are at high risk of developing type 2 diabetes, while the exact mechanisms underlying its pathophysiology are still unclear. We investigated the association of glucagon-like peptide-1 (GLP-1) response to oral glucose with parameters of glycemic control in women with previous GDM in the prospective PPSDiab (Prediction, Prevention, and Subclassification of Type 2 Diabetes) study.

Research design and methods: Glucose metabolism parameters and GLP-1 secretion were analyzed during oral glucose tolerance test (OGTT) in women with previous GDM (n=129) and women with a history of normal glucose tolerance (n=67) during pregnancy (controls). First- and second-phase insulin and GLP-1 secretion in relation to plasma glucose (PG) levels were assessed, and development of pre-diabetes was analyzed after 5-year follow-up among women with previous GDM and a normal glycemic state at baseline (n=58).

Results: The area under the curve (AUC during the OGTT 0-120 min) of PG and insulin but not GLP-1 differed significantly between post-GDM women and controls. However, women with previous GDM had a significantly decreased GLP-1 response in relation to PG and plasma insulin during the second phase of the OGTT. After a follow-up of 5 years, 19.0% post-GDM women with a normal glycemic state at the baseline visit developed abnormal glucose metabolism. The total, first- and second-phase AUC GLP-1/PG and GLP-1/insulin ratios were not associated with development of abnormal glucose tolerance.

Conclusions: Women with previous GDM showed a reduced GLP-1 response in relation to PG and insulin concentrations indicating early abnormalities in glucose metabolism. However, the altered GLP-1 response to oral glucose did not predict progression to pre-diabetes and type 2 diabetes in the first 5 years after GDM.

Introduction: Insulin resistance and defects in pancreatic beta cells are the two major pathophysiologic abnormalities that underlie type 2 diabetes. In addition, visceral fat area (VFA) is reported to be a stronger predictor for diabetes than body mass index (BMI). Here, we tested whether the performance of diabetes prediction models could be improved by adding HOMA-IR and HOMA-β and replacing BMI with VFA.

Research design and methods: We developed five prediction models using data from a cohort study (5578 individuals, of whom 94.7% were male, and 943 had incident diabetes). We conducted a baseline model (model 1) including age, sex, BMI, smoking, dyslipidemia, hypertension, and HbA1c. Subsequently, we developed another four models: model 2, predictors in model 1 plus fasting plasma glucose (FPG); model 3, predictors in model 1 plus HOMA-IR and HOMA-β; model 4, predictors in model 1 plus FPG, HOMA-IR, and HOMA-β; model 5, replaced BMI with VFA in model 2. We assessed model discrimination and calibration for the first 10 years of follow-up.

Results: The addition of FPG to model 1 obviously increased the value of the area under the receiver operating characteristic curve from 0.79 (95% CI 0.78, 0.81) to 0.84 (0.83, 0.85). Compared with model 1, model 2 also significantly improved the risk reclassification and discrimination, with a continuous net reclassification improvement index of 0.61 (0.56, 0.70) and an integrated discrimination improvement index of 0.09 (0.08, 0.10). Adding HOMA-IR and HOMA-β (models 3 and 4) or replacing BMI with VFA (model 5) did not further materially improve the performance.

Conclusions: This cohort study, primarily composed of male workers, suggests that a model with BMI, FPG, and HbA1c effectively identifies those at high diabetes risk. However, adding HOMA-IR, HOMA-β, or replacing BMI with VFA does not significantly improve the model. Further studies are needed to confirm our findings.