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. 2022 Jan 15:237:122916.
doi: 10.1016/j.talanta.2021.122916. Epub 2021 Oct 5.

Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications

Zozan Guleken  1 , Paweł Jakubczyk  2 , Paja Wiesław  2 , Pancerz Krzysztof  3 , Huri Bulut  4 , Esra Öten  5 , Joanna Depciuch  6 , Nevzat Tarhan  7
Affiliations

Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications

Zozan Guleken et al. Talanta. .

Abstract

Herein, we show differences in blood serum of asymptomatic and symptomatic pregnant women infected with COVID-19 and correlate them with laboratory indexes, ATR FTIR and multivariate machine learning methods. We collected the sera of COVID-19 diagnosed pregnant women, in the second trimester (n = 12), third-trimester (n = 7), and second-trimester with severe symptoms (n = 7) compared to the healthy pregnant (n = 11) women, which makes a total of 37 participants. To assign the accuracy of FTIR spectra regions where peak shifts occurred, the Random Forest algorithm, traditional C5.0 single decision tree algorithm and deep neural network approach were used. We verified the correspondence between the FTIR results and the laboratory indexes such as: the count of peripheral blood cells, biochemical parameters, and coagulation indicators of pregnant women. CH2 scissoring, amide II, amide I vibrations could be used to differentiate the groups. The accuracy calculated by machine learning methods was higher than 90%. We also developed a method based on the dynamics of the absorbance spectra allowing to determine the differences between the spectra of healthy and COVID-19 patients. Laboratory indexes of biochemical parameters associated with COVID-19 validate changes in the total amount of proteins, albumin and lipase.

Keywords: COVID-19; FTIR; Laboratory indexes; Machine learning; Pregnancy.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Levels of albumin and total protein (g/dL). * Compared to the T2, + compared to T3. *p < 0.05, **p < 0.01, +p < 0.05, ++p<0.01 were considered significant.
Fig. 2
Fig. 2
Representative FTIR spectra of serum collected from COVID-19 infected pregnant women: T2 (black spectrum); T3 (red spectrum); T2s (blue spectrum) and without COVID-19 disease (green spectrum).
Fig. 3
Fig. 3
Deconvolution of the amide I band of serum collected from COVID-19 infected pregnant women: T2 (a); T3 (b); T2s (c) and without COVID-19 disease (d).
Fig. 4
Fig. 4
PLS plot with the marked line separating the wavenumber values statistically significant in distinguishing between control and COVID samples.
Fig. 5
Fig. 5
Diagram of a decision tree built from a full two-class set.
See this image and copyright information in PMC

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