ArticleAmerican journal of obstetrics and gynecology2022
Latent class analysis of placental histopathology: a novel approach to classifying early and late preterm births.
Article in American journal of obstetrics and gynecology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Phenotypic subclassification of preeclampsia through cluster analysis of preterm birth-related factors.BMC medical informatics and decision making · 2026Article
- Placental pathologic score 1-2 subclinical abnormalities and early neonatal clinical indicators in term infants: a retrospective study.American journal of translational research · 2026Article
- Predicting Spontaneous Preterm Birth Using the Immunome.Clinics in perinatology · 2024Review
- Relationship between placental pathology and neonatal outcomes.Frontiers in pediatrics · 2023Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundNeonatal morbidity attributable to prematurity predominantly occurs among early preterm births (<32 weeks) rather than late preterm births (32 to <37 weeks). Methods to distinguish early and late preterm births are lacking given the heterogeneity in pathophysiology and risk factors, including maternal obesity. Although preterm births are often characterized by clinical presentation (spontaneous or clinically indicated), classifying deliveries by placental features detected on histopathology reports may help identify subgroups of preterm births with similar etiology and risk factors. Latent class analysis is an empirical approach to characterize preterm births on the basis of observed combinations of placental features.
objectiveTo identify histopathologic markers that can distinguish early (<32 weeks) and late preterm births (32 to <37 weeks) that are also associated with maternal obesity and neonatal outcomes. STUDY
designWomen with a singleton preterm birth at University of Pittsburgh Medical Center Magee-Womens Hospital (Pittsburgh, PA) from 2008 to 2012 and a placental evaluation (89% of preterm births) were stratified into early (n=900, 61% spontaneous) and late preterm births (n=3362, 57% spontaneous). Prepregnancy body mass index was self-reported at first prenatal visit and 16 abstracted placental features were analyzed. Placental subgroups (ie, latent classes) of early and late preterm births were determined separately by latent class analysis of placental features. The optimal number of latent classes was selected by comparing fit statistics. The probability of latent class membership across prepregnancy body mass indexes was estimated in early preterm births and in late preterm births by an extension of multinomial regression called pseudo-class regression, adjusting for race, smoking, education, and parity. The frequencies of severe neonatal morbidity (composite outcome: respiratory distress, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, periventricular leukomalacia, patent ductus arteriosus, and retinopathy of prematurity), small-for-gestational-age, and length of neonatal intensive care unit stay were compared across latent classes by chi-square and Kruskal-Wallis tests.
resultsEarly preterm births were grouped into 4 latent classes based on placental histopathologic features: acute inflammation (38% of cases), maternal vascular malperfusion with inflammation (29%), maternal vascular malperfusion (25%), and fetal vascular thrombosis with hemorrhage (8%). As body mass index increased from 20 to 50kg/m
conclusionObesity may predispose women to early but not late preterm birth through placental vascular impairment. Latent class analysis of placental histopathologic data provides an evidence-based approach to group preterm births with shared underlying etiology and risk factors.
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