Abstract：
:Gestational diabetes mellitus (GDM) is a hyperglycaemic imbalance first recognized during pregnancy, and affects up to 22% of pregnancies worldwide, bringing negative maternal-fetal consequences in the short- and long-term. In order to better characterize GDM in pregnant women, 100 blood plasma samples (50 GDM and 50 healthy pregnant control group) were submitted Attenuated Total Reflection Fourier-transform infrared (ATR-FTIR) spectroscopy, using chemometric approaches, including feature selection algorithms associated with discriminant analysis, such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and Support Vector Machines (SVM), analyzed in the biofingerprint region between 1800 and 900 cm-1 followed by Savitzky-Golay smoothing, baseline correction and normalization to Amide-I band (~ 1650 cm-1). An initial exploratory analysis of the data by Principal Component Analysis (PCA) showed a separation tendency between the two groups, which were then classified by supervised algorithms. Overall, the results obtained by Genetic Algorithm Linear Discriminant Analysis (GA-LDA) were the most satisfactory, with an accuracy, sensitivity and specificity of 100%. The spectral features responsible for group differentiation were attributed mainly to the lipid/protein regions (1462-1747 cm-1). These findings demonstrate, for the first time, the potential of ATR-FTIR spectroscopy combined with multivariate analysis as a screening tool for fast and low-cost GDM detection.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Bernardes-Oliveira E,de Freitas DLD,de Morais CLM,Cornetta MDCM,Camargo JDAS,de Lima KMG,Crispim JCOdoi
10.1038/s41598-020-75539-ysubject
Has Abstractpub_date
2020-11-06 00:00:00pages
19259issue
1issn
2045-2322pii
10.1038/s41598-020-75539-yjournal_volume
10pub_type
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