Maternal thyroid profile in first and second trimester of pregnancy is correlated with gestational diabetes mellitus through machine learning. (1st January 2021)

• Record Type: Journal Article
• Authors: Araya, Juan; Rodriguez, Andrés; Lagos-SanMartin, Karin; Mennickent, Daniela; Gutiérrez-Vega, Sebastián; Ortega-Contreras, Bernel; Valderrama-Gutiérrez, Barbara; Gonzalez, Marcelo; Farías-Jofré, Marcelo; Guzmán-Gutiérrez, Enrique
• Is Part Of: Placenta. Volume 103(2021)
• Page Start: 82
• Page End: 85
• Publication Date: 2021-01-01
• Subjects: Machine learning -- Gestational diabetes mellitus -- Thyroid hormones -- Principal component analysis; Placenta -- Periodicals; Reproduction -- Periodicals; Placenta -- Periodicals; Placenta -- Périodiques; Reproduction -- Périodiques; 612.63
• DOI: 10.1016/j.placenta.2020.10.015
• Languages: English
• ISSNs: 0143-4004

Abstract

Abstract: There is evidence about a possible relationship between thyroid abnormalities and gestational diabetes mellitus (GDM). However, there is still no conclusive data on this dependence, since no strong correlation has been proved. In this work, we used machine learning to determine whether there is a correlation between maternal thyroid profile in first and second trimester of pregnancy and GDM. Using principal component analysis, it was possible to find an evident correlation between both, which could be used as a complement for a more sensitive GDM diagnosis. Highlights: There is a correlation between a defined thyroidal pattern and Gestational Diabetes. A Machine Learning technique allowed to identify the thyroidal pattern. A multivariate pattern can be used to improve gestational diabetes diagnosis.