2022
DOI: 10.3389/fendo.2022.817595
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Identifying Non-Linear Association Between Maternal Free Thyroxine and Risk of Preterm Delivery by a Machine Learning Model

Abstract: ObjectivePreterm delivery (PTD) is the primary cause of mortality in infants. Mounting evidence indicates that thyroid dysfunction might be associated with an increased risk of PTD, but the dose-dependent association between the continuous spectrum maternal free thyroxine (FT4) and PTD is still not well-defined. This study aimed to further investigate this relationship using a machine learning-based model.MethodsA hospital-based cohort study was conducted from January 2014 to December 2018 in Shanghai, China. … Show more

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Cited by 4 publications
(3 citation statements)
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References 47 publications
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“…Notably, our MR analyses provide evidence suggesting that maternal TSH levels during pregnancy may potentially influence gestational duration, although the effect may be nonlinear. Notably, genetically predicted higher maternal TSH are nominally associated with a heightened risk of preterm birth, and previous research has demonstrated a U-shaped association between FT4 levels and preterm birth[50]. Further validation through intervention studies is warranted to ascertain the genuine effects.…”
Section: Discussionmentioning
confidence: 99%
“…Notably, our MR analyses provide evidence suggesting that maternal TSH levels during pregnancy may potentially influence gestational duration, although the effect may be nonlinear. Notably, genetically predicted higher maternal TSH are nominally associated with a heightened risk of preterm birth, and previous research has demonstrated a U-shaped association between FT4 levels and preterm birth[50]. Further validation through intervention studies is warranted to ascertain the genuine effects.…”
Section: Discussionmentioning
confidence: 99%
“…The machine-learning models used were generalized additive models (statistic modeling technique used to analyze the relationship between response and predictor variables) with penalized cubic regression spline (non-parametric method of regression modelling) to explore the non-linear association between maternal thyroid hormone (T4) and risk of PTB. The data were gathered through history taking and blood draw in antenatal clinics by midwives and obstetricians [152]. The time-to-event method and multivariable cox proportional hazard model (regression model investigating the length of time) were further applied to look more closely at the possible association between very high and low maternal T4 concentrations with the timing of PTL.…”
Section: Machine Learningmentioning
confidence: 99%
“…Through this work, they identified a U-shaped association between maternal T4 and gestational age at delivery but found no evidence of thyroid disease being a risk factor for PTB. This suggests that though thyroid pathology may not be linked with PTB, serum-free T4 level may be a useful marker for a screening test to identify women at risk of PTB [152].…”
Section: Machine Learningmentioning
confidence: 99%