4.3 Article

Machine learning-based placental clusters and their associations with adverse pregnancy outcomes

Journal

PAEDIATRIC AND PERINATAL EPIDEMIOLOGY
Volume 37, Issue 4, Pages 350-361

Publisher

WILEY
DOI: 10.1111/ppe.12938

Keywords

cluster analysis; fetal growth; placenta; pregnancy outcome; stillbirth; unsupervised machine learning

Ask authors/readers for more resources

This study investigates the associations between co-occurring placental features and adverse pregnancy outcomes. The study finds that co-occurring placental abnormalities are related to adverse pregnancy outcomes, with severe maternal vascular malperfusion having the highest risk among the analyzed clusters.
BackgroundPlacental abnormalities have been described in clinical convenience samples, with predominately adverse outcomes. Few studies have described placental patterns in unselected samples. ObjectiveWe aimed to investigate associations between co-occurring placental features and adverse pregnancy outcomes in a prospective cohort of singletons. MethodsData were from the Safe Passage study (U.S. and South Africa, 2007-2015). Before 24 weeks' gestation, participants were randomly invited to donate placental tissue at delivery for blinded, standardised pathological examination. We used hierarchical clustering to construct statistically derived groups using 60 placental features. We estimated associations between the placental clusters and select adverse pregnancy outcomes, expressed as unadjusted and adjusted risk ratios (RRs) and robust 95% confidence intervals (CI). ResultsWe selected a 7-cluster model. After collapsing 2 clusters to form the reference group, we labelled the resulting 6 analytic clusters according to the overarching category of their most predominant feature(s): severe maternal vascular malperfusion (n = 117), fetal vascular malperfusion (n = 222), other vascular malperfusion (n = 516), inflammation 1 (n = 269), inflammation 2 (n = 175), and normal (n = 706). Risks for all outcomes were elevated in the severe maternal vascular malperfusion cluster. For instance, in unadjusted analyses, this cluster had 12 times the risk of stillbirth (RR 12.07, 95% CI 4.20, 34.68) and an almost doubling in the risk of preterm delivery (RR 1.93, 95% CI 1.27, 2.93) compared with the normal cluster. Small infant size was more common among the abnormal clusters, with the highest unadjusted RRs observed in the fetal vascular malperfusion cluster (small for gestational age birth RR 2.99, 95% CI 2.24, 3.98, head circumference <10th percentile RR 2.86, 95% CI 1.60, 5.12). Upon adjustment for known risk factors, most RRs attenuated but remained >1. ConclusionOur study adds to the growing body of epidemiologic research, finding adverse pregnancy outcomes may occur through etiologic mechanisms involving co-occurring placental abnormalities.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available