Faculty of Environment and Life Sciences, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100124, China.
Haidian Maternal and Children Health Hospital, Beijing, 100080, China.
Technol Health Care. 2021;29(S1):57-63. doi: 10.3233/THC-218006.
Oral glucose tolerance test (OGTT) is a standard for the diagnosis of gestational diabetes mellitus (GDM). However, clinically, some cases with normal results were diagnosed as GDM in the third trimester.
To establish a risk model based on energy metabolism, epidemiology, and biochemistry that could predict the GDM pregnant women with normal OGTT results in the second trimester.
Qualitative and quantitative data were analyzed to find out the risk factors, and the binary logistic backward LR regression was used to establish the prediction model of each factor and comprehensive factor, respectively.
The risk factors including the rest energy expenditure per kilogram of body weight, oxygen consumption per kilogram of body weight, if more than the weight gain criteria of the Institute of Medicine, the increase of body mass index between the second trimester and pre-pregnancy, and fasting blood glucose. By comparison, the comprehensive model had the best prediction performance, indicating that 85% of high-risk individuals were correctly classified.
Energy metabolism, epidemiology, and biochemistry had better recognition ability for the GDM pregnant women with normal OGTT results in the second trimester. The addition of metabolic factors in the second trimester also improved the overall prediction performance.
口服葡萄糖耐量试验（OGTT）是诊断妊娠期糖尿病（GDM）的标准。然而，临床上有些结果正常的病例在孕晚期被诊断为 GDM。
建立一个基于能量代谢、流行病学和生物化学的风险模型，以预测孕中期 OGTT 结果正常的 GDM 孕妇。
对定性和定量数据进行分析，找出危险因素，并分别采用二项逻辑向后 LR 回归建立各因素和综合因素的预测模型。
包括每公斤体重静息能量消耗、每公斤体重耗氧量、体重增加超过医学研究所标准、孕中期至孕前体重指数增加和空腹血糖在内的危险因素。相比之下，综合模型具有最佳的预测性能，表明 85%的高危个体得到了正确分类。
能量代谢、流行病学和生物化学对孕中期 OGTT 结果正常的 GDM 孕妇具有更好的识别能力。在孕中期加入代谢因素也提高了整体预测性能。
