Predictability of HOMA-IR for Gestational Diabetes Mellitus in Early Pregnancy Based on Different First Trimester BMI Values

基于不同孕早期BMI值的HOMA-IR对妊娠早期糖尿病的预测价值

阅读:1

Abstract

Objective: To investigate the ability of homeostasis model assessment of insulin resistance (HOMA-IR) in early pregnancy for predicting gestational diabetes mellitus (GDM) in Chinese women with different first-trimester body mass index (FT-BMI) values. Methods: Baseline characteristics and laboratory tests were collected at the first prenatal visit (6−12 weeks of gestation). GDM was diagnosed by a 75 g oral glucose tolerance test (OGTT) at 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression were applied to identify the association between HOMA-IR and GDM. The cutoff points for predicting GDM were estimated using receiver operating characteristic (ROC) curve analysis. Results: Of the total of 1343 women, 300 (22.34%) were diagnosed with GDM in the 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression verified HOMA-IR as a significant risk factor for GDM in the normal weight subgroup (FT-BMI < 24 kg/m2) (adjusted OR 2.941 [95% CI 2.153, 4.016], P < 0.001), overweight subgroup (24.0 kg/m2 ≤ FT-BMI < 28.0 kg/m2) (adjusted OR 3.188 [95% CI 2.011, 5.055], P < 0.001), and obese subgroup (FT-BMI ≥ 28.0 kg/m2) (adjusted OR 9.415 [95% CI 1.712, 51.770], p = 0.01). The cutoff values of HOMA-IR were 1.52 (area under the curve (AUC) 0.733, 95% CI 0.701−0.765, p < 0.001) for all participants, 1.43 (AUC 0.691, 95% CI 0.651−0.730, p < 0.001) for normal weight women, 2.27 (AUC 0.760, 95% CI 0.703−0.818, p < 0.001) for overweight women, and 2.31 (AUC 0.801, 95% CI 0.696−0.907, p < 0.001) for obese women. Conclusions: Increased HOMA-IR in early pregnancy is a risk factor for GDM, and HOMA-IR can be affected by body weight. The cutoff value of HOMA-IR to predict GDM should be distinguished by different FT-BMI values.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。