PDF(Pubmed)
Abstract：
Gestational diabetes mellitus (GDM) is a hyperglycemic state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, has low reproducibility, and results are tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to produce a result. Near-infrared (NIR) spectroscopy is a simple, fast, and low-cost analytical technique that has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and duration of analysis. Serum samples from the first trimester (before GDM diagnosis) and the second trimester (at the time of GDM diagnosis) of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 mathematical pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best models for first and second trimester achieved areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR-spectroscopy-based methods for the prediction of GDM. The developed methods allow for prediction of GDM from 10 µL of serum in only 32 min. They are simple, fast, and have a great potential for application in clinical practice, especially as alternative screening tools to the OGTT for GDM diagnosis.
摘要：
妊娠期糖尿病（GDM）是一种高血糖状态，通常通过口服葡萄糖耐量试验（OGTT）来诊断，这是令人不快的，耗时,重现性低，结果很慢。已提出用于改善GDM诊断的机器学习（ML）预测模型通常基于花费数小时才能产生结果的仪器方法。近红外(NIR)光谱是一种简单的,快,以及从未评估过GDM预测的低成本分析技术。本研究旨在开发基于近红外光谱的GDMML预测模型，并根据其预测能力和分析持续时间评估其作为早期检测或替代筛查工具的潜力。通过NIR光谱分析妊娠的前三个月（GDM诊断前）和第二个三个月（GDM诊断时）的血清样品。考虑了四个光谱范围，并对每种进行了80种数学预处理。使用单块和多块ML技术建立了基于NIR数据的模型。每个模型都经过双重交叉验证。第一和第二三个月的最佳模型在接收器工作特性曲线下的面积分别为0.5768±0.0635和0.8836±0.0259。这是第一项报告基于近红外光谱的GDM预测方法的研究。开发的方法允许仅在32分钟内从10µL血清中预测GDM。它们很简单，快,并在临床实践中具有巨大的应用潜力，特别是作为GDM诊断的OGTT的替代筛查工具。
