Beijing An Zhen Hospital, Capital Medical University, The Key Laboratory of Remodeling-related Cardiovascular Diseases, Ministry of Education, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China; Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA.
Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA.
Diabetes Res Clin Pract. 2014 Aug;105(2):245-50. doi: 10.1016/j.diabres.2014.04.014. Epub 2014 Apr 30.
We designed a study to compare the predictive power of static and dynamic insulin resistance indices for categorized pre-diabetes (PDM)/type 2 diabetes (DM).
Participants included 1134 adults aged 18-60 years old with normal glucose at baseline who completed both baseline and 6-years later follow-up surveys. Insulin resistance indices from baseline data were used to predict risk of PDM or DM at follow-up. Two static indices and two dynamic indices were calculated from oral glucose tolerance test results (OGTT) at baseline. Area under the receiver operating characteristic curve (AROC) analysis was used to estimate the predictive ability of candidate indices to predict PDM/DM. A general estimation equation (GEE) model was applied to assess the magnitude of association of each index at baseline with the risk of PDM/DM at follow-up.
The dynamic indices displayed the largest and statistically predictive AROC for PDM/DM diagnosed either by fasting glucose or by postprandial glucose. The bottom quartiles of the dynamic indices were associated with an elevated risk of PDM/DM vs. the top three quartiles. However, the static indices only performed significantly to PDM/DM diagnosed by fasting glucose.
Dynamic insulin resistance indices are stronger predictors of future PDM/DM than static indices. This may be because dynamic indices better reflect the full range of physiologic disturbances in PDM/DM.
我们设计了一项研究，旨在比较静态和动态胰岛素抵抗指数对分类前驱糖尿病（PDM）/2 型糖尿病（DM）的预测能力。
参与者包括 1134 名年龄在 18-60 岁之间的成年人，基线时血糖正常，完成了基线和 6 年后的随访调查。使用基线数据中的胰岛素抵抗指数来预测随访时发生 PDM 或 DM 的风险。从基线时的口服葡萄糖耐量试验（OGTT）结果中计算出两种静态指数和两种动态指数。使用受试者工作特征曲线（ROC）下面积（AUC）分析来评估候选指数预测 PDM/DM 的能力。应用一般估计方程（GEE）模型来评估基线时每个指数与随访时 PDM/DM 风险之间的关联程度。
动态指数对空腹血糖或餐后血糖诊断的 PDM/DM 显示出最大和统计学上具有预测性的 ROC。与前三分之一相比，动态指数的底部四分位数与 PDM/DM 的风险升高相关。然而，静态指数仅对空腹血糖诊断的 PDM/DM 具有显著作用。
动态胰岛素抵抗指数是未来 PDM/DM 的更强预测因子，这可能是因为动态指数更好地反映了 PDM/DM 中生理紊乱的全部范围。
