Abstract
BACKGROUND: Neonatal 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. OBJECTIVE: To 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 DESIGN: Women 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. RESULTS: Early 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(2), the probability of maternal vascular malperfusion and fetal vascular thrombosis with hemorrhage increased, whereas the probability of maternal vascular malperfusion with inflammation decreased. There was minimal change in the probability of acute inflammation with increasing body mass index. Late preterm births also had 4 latent classes: maternal vascular malperfusion (22%), acute inflammation (12%), fetal vascular thrombosis with hemorrhage (9%), and low-risk pathology (58%). Body mass index was not associated with major changes in likelihood of the latent classes in late preterm births. Associations between body mass index and likelihood of the latent classes were not modified by type of delivery (spontaneous or indicated) in early or late preterm births. Maternal malperfusion and fetal vascular thrombosis with hemorrhage were associated with greater neonatal morbidity than the other latent classes in early and late preterm births. CONCLUSION: Obesity 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.