Latent class analysis of placental histopathology: a novel approach to classifying early and late preterm births

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), smallness 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/m², 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.

Introduction

In the United States, approximately 80% of preterm births (PTBs) are late PTBs (32 to <37 weeks of gestation), but 75% of neonatal deaths among PTBs occur in early PTBs (<32 weeks).¹ Early and late PTB may have distinct risk factors (eg, maternal obesity) with variable pathophysiology.² In addition, PTBs are classified as spontaneous or clinically indicated PTBs.³ Yet, this classification is not informative of PTB etiology and findings between clinical classification and neonatal morbidity risk are conflicting.^3–5 Placental histopathologic evaluations are routinely conducted to inform clinicians’ assessments of PTB causes.⁶ These evaluations are an underutilized resource for understanding the pathophysiology and neonatal sequelae of early and late PTBs.

Interpreting placental histopathology is challenging because findings can be incidental or related to physiological processes like labor.^7–9 A high proportion (28%—78%) of uncomplicated term pregnancies are reported to have at least 1 histopathologic feature.^10–11 In the absence of an approach to distinguish healthy from complicated placentas’ histopathology offers limited insight for pediatric follow-up. Clusters of histopathologic features may be more reflective than single measures of true pathology and prognostic of neonatal outcomes.

Various approaches have previously classified PTBs by patterns of histopathologic features. Previous approaches have been based on anticipated groupings of histopathology (eg, inflammatory or vascular impairment) using correlative measures, factor analysis, and predefined groups based on expert opinion.^12–15 These methods may presuppose placental pathology groups, miss key histopathologic features and/or lack strong associations with clinical outcomes. Empirical classification, as applied here, may identify novel placental histopathologic patterns in PTB.^16–18

Latent class analysis (LCA) is a statistical method that classifies individuals into groups based on different patterns of observed data.¹⁹ Groups are called latent classes because they are estimated, not directly measured. For example, grouping individuals into personality types based on survey response patterns. LCA is appealing over other clustering methods (eg, hierarchical or k-means clustering) because standard model fit statistics inform the appropriate number of latent classes, LCA allows missing data, and latent classes are easy to interpret.^18,19 Covariates can be added to LCA models to test if risk factors like obesity predict latent class membership.^19–21

We aimed to: (1) classify early and late PTBs into placental latent classes based on observed patterns of placental histopathologic features by LCA and (2) determine if prepregnancy body mass index (BMI) was associated with specific latent classes. We focused on prepregnancy BMI because our approach may help understand inconsistent findings on obesity and PTB.²² Evidence suggests obesity is associated with an increased risk of early PTB (<32 weeks), but not late PTB.^2,23 Obesity may alter the risk of early and late PTB by different placental mechanisms.^24–26 For clinical relevance of our classification approach, we compared the prevalence of severe neonatal morbidity (composite outcome: respiratory distress syndrome, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, patent ductus arteriosus, periventricular leukomalacia, retinopathy of prematurity), length of neonatal intensive care unit (NICU) stay, and smallness for gestational age (SGA) across latent classes.

Materials and Methods

Study participants

Delivery data were collected from the Magee Obstetric Maternal & Infant (MOMI) database. We included live singleton early (20 to <32 weeks) and late PTBs (32 to <37 weeks) delivered between 2008 and 2012 with available placental pathology data (94% of early PTBs and 88% of late PTBs). We excluded stillbirths (0.5% of PTBs) because our automated placental report abstraction approach did not reliably distinguish placental findings. Women with multifetal gestations were excluded because placental findings in multifetal pregnancies are different from those of singleton pregnancies, and placental findings were unable to be linked to each ^-fetus.^27,28 The University of Pittsburgh Institutional Review Board approved this project (STUDY20050303), and no consent was needed because data were deidentified.

Placental data

Placental histopathologic features considered for LCA were extracted from pathology reports conducted by 2 placental pathologists following a standardized protocol and linked to the MOMI database by an automated process previously described.²⁹ Histopathology definitions were adapted from the 2014 Amsterdam criteria (Supplemental Table 1).^30,31 Pathologic features included markers of inflammation (acute chorioamnionitis, vasculitis, funisitis, deciduitis, villitis, intervillitis), maternal vascular malperfusion (MVM: villous infarct, intra- parenchymal hemorrhage, subchorionic hemorrhage, advanced villous maturation, decidual vasculopathy, villous agglutination, intervillous thrombus), fetal vascular malperfusion (avascular villi, stromal-vascular karyorrhexis, fetal vascular thrombosis, chorangiosis), and other markers (placental growth, chorioangioma, chorangiomatosis, delayed villous maturation, dysmaturity). Stromal-vascular karyorrhexis and avascular villi were combined given that stromal-vascular karyorrhexis progresses to avascular villi.³² There was excellent agreement for review of placental slides between clinical pathology reports and a pathologist blinded to all clinical information except gestational age (W.T.P) for features of inflammation (82%)¹³ and MVM (kappa=0.78).³³

Anthropometry

Prepregnancy BMI was calculated as a ratio of weight (kg) to height (m) squared (kg/m²) using self-reported data at first prenatal visit. Self-reported pre-pregnancy weight was highly correlated with first measured weight in pregnancy (r=0.99) at UPMC Magee-Womens Hospital.³⁴

Pregnancy characteristics

Gestational age was determined using best obstetrical estimates based on first/ second trimester ultrasound in conjunction with last menstrual period.³⁵ Pregnancy and neonatal outcomes were extracted from medical records based on International Classification of Diseases, Ninth Revision codes provided in the Supplemental Methods sections. Pregnancy complications included gestational diabetes mellitus, gestational hypertension, preeclampsia/eclampsia, cervical shortening, clinical chorioamnionitis, and preterm premature rupture of membranes (PPROM). PTBs were classified as early PTB for deliveries <32 weeks of gestation and late PTB for deliveries at 32 to <37 weeks.³ Early PTBs were not further classified because there were few PTBs at <28 weeks (n=374, 7.8% of PTBs), and PTBs at <32 weeks are postulated to have similar etiologies.^3,36 A spontaneous PTB was defined as a pregnancy with spontaneous onset of contractions or premature rupture of fetal membranes before 37 weeks (irrespective of induction or cesarean delivery after labor). A clinically indicated PTB was defined as an induced pregnancy or cesarean delivery before 37 weeks.³⁷ Adverse neonatal outcomes included SGA (birthweight <10th percentile using the Alexander birthweight curve),³⁸ length of NICU stay (infant hospital discharge date minus date of delivery), and a composite score for severe neonatal morbidity: respiratory distress syndrome, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, periventricular leukomalacia, patent ductus arteriosus, and retinopathy of prematurity.

Statistical analyses

Frequencies of individual placental features were compared between early and late PTBs by chi-square and Fisher exact tests. Early (<32 weeks) and late (32 to <37weeks) PTBs were analyzed separately for: (1) grouping deliveries into classes reflective of distinct placental pathology, (2) predicting class membership across prepregnancy BMI, and (3) comparing clinical outcomes across classes.

Deliveries were classified on the basis of observed patterns of 16 placental histopathologic features using LCA. We call these groups placental latent classes because they are empirically derived from observed histopathology patterns, and not directly measured by the pathologist. Rare placental features (< 1% of PTBs) were excluded because of limited numbers. The optimal number of placental latent classes in early and late PTBs was determined by comparing 6 models ranging from 1 to 6 latent classes using model fit statistics. We excluded models that generated rare latent classes (<5%) and models with poor entropy (<0.70), a measure of how accurately pregnancies are classified.^18,39 Latent classes were labeled on the basis of the combination of placental features with probabilities of occurring >25% within that class. Among late PTBs, we excluded deliveries at 36 weeks as a sensitivity analysis to assess the effect of PTB misclassification attributable to potential inaccurate dating. Few women (4.5%) had more than 1 pregnancy in the cohort. Restricting to the first pregnancy did not change the number or composition of placental features within latent classes. Therefore, we included all pregnancies in the analysis.

We evaluated if prepregnancy BMI was associated with likelihood of the placental latent classes by 4 regression methods (pseudo-class, most-likely class, probability-weighted, and single-step latent class regression) described in the Supplemental Methods section.^20,40 Briefly, latent classes are statistically estimated; therefore, pregnancies maybe misclassified. Misclassification adds variability that is accounted for by these regression methods. Assessing consistency in findings across methods helps identify if errors were introduced by the estimation method. Pseudo-class regression is the preferred method because it adequately accounts for variability from potential latent class misclassification and is flexible in handling missing data.²⁰ Associations were visualized by predicted probability plots. Models were adjusted for maternal race, education, parity, and smoking. We examined whether associations between BMI and likelihood of latent classes were modified by interaction with clinical presentation of PTB (spontaneous vs indicated), race, and fetal sex.^41,42 For any variable found to be an effect modifier (P<.10), stratified results are presented.

We compared the proportions of pregnancy complications and neonatal morbidities across placental latent classes (deliveries assigned to most-likely latent class) by chi-square and Fisher exact tests for categorical outcomes and Kruskal-Wallis tests for continuous outcomes. An alpha level of 0.05 was assumed for nominal significance and a Bonferroni-corrected alpha was used for significance after multiple comparisons of pregnancy (0.05/8=0.006) and neonatal outcomes (0.05/10=0.005).

Prepregnancy BMIs were missing in 42% of PTBs. Women with and without a reported prepregnancy BMI had comparable maternal and pathology characteristics (Supplemental Tables 2 and 3). Missing data were imputed by multiple imputation with chained equations.⁴³ We compared regression estimates by complete-case analysis and by imputation to assess sensitivity to missingness. Additional details are provided in the Supplemental Methods section. Analyses were conducted in RStudio (RStudio, Boston, MA).⁴⁴

Results

There were 4262 liveborn singleton PTBs with placental histopathology at UPMC Magee-Womens Hospital between 2008 and 2012; 20% were early PTBs (<32 weeks) and 80% were late PTBs (32 to <37 weeks) (Figure 1). Women with early PTBs were younger, more likely to be Black, less likely to have a college education, and less likely to have diabetes mellitus (preexisting or gestational) than women with late PTB (Table 1). Women with early PTB were more likely to have PPROM and spontaneous PTB, and less likely to have a small-for-gestational-age baby than women with late PTB. There were 797 (89%) early PTBs and 2392 (71%) late PTBs with at least 1 placental histopathologic feature. Early PTBs had higher frequencies of histopathologic features of acute inflammation and MVM than late PTBs (Figure 2).

FIGURE 1. Study selection criteria.

Inclusion and exclusion criteria for study population.

PTB, preterm birth.

Layden et al. Latent class analysis of early and late preterm births. Am J Obstet Gynecol 2022.

TABLE 1.

Maternal and delivery characteristics for early (n=900) and late preterm births (n=3362)^a,b

Maternal characteristics	Missing (n)	Early PTB (20 to <32 wk)	Missing (n)	Late PTB (32 to <37 wk)	P value
Maternal age (y)	0	27.3±6.3	0	28.4±6.2	<.001
Race, n (%)	5		14		.003
White		613 (68.5)		y 2434 (72.7)
Black		255 (28.5)		780 (23.3)
Other		27 (3.0)		134(4.0)
Education, n (%)	20		33		<.001
High school/GED or less		432 (49.1)		1263 (37.9)
Some college		448 (50.9)		2066 (62.1)
Prepregnancy BMI, kg/m2	445	26.9±7.5	1365	26.3±6.8	.274
Weight status, n (%)	445		1365		.162
Underweight (<18.5 kg/m2)		30 (6.6)		109(5.5)
Lean (18.5 to <25 kg/m2)		203 (44.6)		939 (47.0)
Overweight (25 to <30 kg/m2)		93 (20.4)		465 (23.3)
Obese (>30 kg/m2)		129 (28.4)		484 (24.2)
Smoking in pregnancy, n (%)	12	214(24.1)	27	774 (23.2)	.608
Nulliparous at enrollment, n (%)	0	463 (51.4)	5	1593 (47.5)	.037
Multiple abortion history, n (%)	0	140 (15.6)	5	487 (14.5)	.462
Diabetes mellitus, n (%)	0		0		<.001
None		821 (91.2)		2851 (84.8)
Preexisting		47 (5.2)		314(9.3)
Gestational		32 (3.6)		197(5.9)
Chronic hypertension, n (%)	0	98 (10.9)	0	280 (8.3)	.020
Hypertensive disorders, n (%)	2		7		.207
No hypertensive disorders		626 (69.7)		2390 (71.2)
Gestational hypertension		26 (2.9)		125 (3.7)
Preeclampsia, HELLP syndrome, eclampsia		246 (27.4)		840 (25.0)
Delivery characteristics
PPROM, n (%) J	1 0	345 (38.3)	0	988 (29.4)	<.001
Clinical presentation, n (%)	3		2		.034
Indicated		350 (39.0)		1446(43.0)
Spontaneous		547 (61.0)		1914(57.0)
Gestational weight gain
Weight gain mean (kg)	494	8.9±6.6	1476	12.8±6.8	<.001
Weight gain Z-score	505	−0.21 ±1.22	1505	−0.10±1.10	.032
Infant birthweight (g)	26	1138±459	14	2493±560	<.001
Smallness for gestational age, n (%)	21	113 (12.9)	13	581 (17.3)	.002
Male fetal sex, n (%)	0	504 (56.0)	0	1821 (54.2)	.345

BMI, body mass index; GED, General Educational Diploma; HELLP, hemolysis, elevated liver enzymes, low platelet count; PPROM, preterm premature rupture of membranes; PTB, preterm birth.

^aContinuous variables are represented as mean±standard deviation;

^bContinuous variables were compared by ttests for normally distributed variables and Mann-Whitney Utests for skewed data. Categorical variables were compared by chi-square tests.

Layden et al. Latent class analysis of early and late preterm births. Am J Obstet Gynecol 2022.

FIGURE 2. Distribution of placental lesions in early and late preterm births.

Proportions of placenta features in early and late preterm births are represented by percentages, with higher percentages graphically represented with a darker red color. There were 175 (4.1%) pregnancies with missing data on placental hypoplasia.

Layden et al. Latent class analysis ofearly and late preterm births. Am J Obstet Gynecol 2022.

On the basis of fit statistics, class size, and classification accuracy, early PTBs were grouped into 4 placental latent classes by LCA (Supplemental Figures 1 and 2). Among early PTBs, 38% had acute inflammation, 29% had MVM with chorioamnionitis, 25% had MVM, and 8% had fetal vascular thrombosis (FVT) with hemorrhage (Figure 3, A). Late PTBs were also grouped into 4 latent classes (Supplemental Figures 1 and 3). Among late PTBs, 58% had low-risk pathology (no pathologic features with >25% probability of occurring for the latent class), 22% had MVM, 12% had acute inflammation, and 9% had FVT with hemorrhage (Figure 3, B). Excluding late PTBs at 36 weeks did not affect the optimal number of latent classes (Supplemental Figure 4).

FIGURE 3. Probabilities of placental features in latent classes of early and late preterm births.

Latent classes and conditional probabilities of placental histopathologic features were identified by latent class analysis of early (A) and late (B) preterm births. Labels for the different latent classes are based on the combination of placental features that have conditional probabilities >25% within the latent class.

adv, advanced; del, delayed; FVT, fetal vascular thrombosis; MVM, maternal vascular malperfusion; vasc, vascular.

Layden et al. Latent class analysis of early and late preterm births. Am J Obstet Gynecol 2022.

Among early PTBs, increasing prepregnancy BMI from 20 to 50kg/m² was associated with a higher probability of MVM (20.2%—37.0%) and FVT with hemorrhage (6.6%—14.9%), and a lower probability of MVM with chorioamnionitis (35.0%—13.2%) after adjusting for race, education, parity, and smoking (Figure 4). There was minimal change in the probability of acute inflammation (38.2%—34.8%) with increasing BMI in early PTBs. In late PTBs, increasing BMI from 20 to 50 kg/ m² was associated with an increased probability of FVT with hemorrhage (7.4%—14.9%) and a decreased probability of low-risk pathology (60.1% —53.0%). There was minimal change in the probabilities of MVM (21.4% —21.7%) and acute inflammation (11.2%—10.4%) with increasing BMI in late PTBs. There were no interactions between BMI and fetal sex, race, or clinical presentation of PTB (spontaneous vs indicated) for early or late PTB. Associations were consistent across early and late PTBs irrespective of regression method or imputation (Supplemental Table 4).

FIGURE 4. Predicted probabilities of placental latent class membership across prepregnancy BMI (kg/m²) in early (A) and late preterm births (B).

Predicted probabilities are derived from pseudo-class regression models adjusted for maternal race, education, smoking, and parity. Predicted probabilities use the average values for the covariates and are based on multiply imputed data (early preterm birth, n = 900; late preterm birth, n = 3362).

BMI, body mass index; FVT, fetal vascular thrombosis; MVM, maternal vascular malperfusion.

Layden et al. Latent class analysis of early and late preterm births. Am J Obstet Gynecol 2022

Among early PTBs, women with acute inflammation were most likely to have a spontaneous delivery (87.5%), PPROM (60.6%), and clinical chorioamnionitis (38.8%) relative to the other latent classes (Table 2). Early PTBs with MVM had the highest frequencies of preeclampsia, eclampsia, and hemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome (79.7%); severe neonatal morbidity (82.0%); and SGA (31.8%) relative to the other latent classes. Among late PTBs, women with acute inflammation had the highest frequencies of spontaneous delivery (75.0%), PPROM (43.6%), and clinical chorioamnionitis (8.7%) compared with the other latent classes (Table 3). Late PTBs with MVM had the highest prevalence of preeclampsia, eclampsia, and HELLP syndrome (53.1%); SGA (42.1%); and longer median NICU stay (9 days; interquartile range, 18 days), whereas women with FVT with hemorrhage had the highest frequency of severe neonatal morbidity (19.9%) relative to the other latent classes.

TABLE 2.

Pregnancy and neonatal outcomes based on placental pathology in early preterm births (n=900)^a,b,c,d

Clinical outcomes	Acute inflammation (n=343)	FVT with hemorrhage (n=71)	MVM (n=202)	MVM with chorioamnionitis (n=284)	Pvalue
Pregnancy outcomes
Diabetes mellitus, n (%)					.115
None	318(92.7)	65 (91.5)	179(88.6)	259 (91.2)
Preexisting	19(5.5)	2 (2.8)	15 (7.4)	11 (3.9)
Gestational	6(1.8)	4 (5.6)	8 (4.0)	14(4.9)
Hypertensive disorders, n (%)					<.001c
No hypertensive disorders	318(93.0)	39 (54.9)	39 (19.3)	230 (81.3)
Gestational hypertension	13 (3.8)	5 (7.0)	2(1.0)	6(2.1)
Preeclampsia, HELLP syndrome, eclampsia	11 (3.2)	27 (38.0)	161 (79.7)	47 (16.6)
Cervical shortening, n (%)	11 (3.2)	0 (0.0)	0 (0.0)	9 (3.2)	.014b
Clinical chorioamnionitis, n (%)	134(38.8)	8 (11.3)	5 (2.5)	25 (8.8)	<.001c
PPROM, n (%)	208 (60.6)	22 (31.0)	20 (9.9)	95 (33.5)	<.001c
Delivery method, n (%)					<.001c
Indicated	43 (12.5)	39 (56.5)	169(83.7)	99 (35.0)
Spontaneous	300 (87.5)	30 (43.5)	33 (16.3)	184(65.0)
Cesarean delivery, n (%)	118(35.9)	48 (68.6)	166 (82.2)	152 (55.9)	<.001c
Male fetal sex, n (%)	188(54.8)	41 (57.7)	104(51.5)	171 (60.2)	.262
Neonatal outcomes
Smallness for gestational age, n (%)	15 (4.5)	14(20.3)	63 (31.8)	21 (7.6)	<.001c
Severe neonatal morbidity, n (%)e	228 (68.1)	49 (71.0)	159 (82.0)	214(76.2)	.004c
Respiratory distress, n (%)	200 (59.7)	43 (62.3)	140 (72.2)	191 (68.0)	.020b
Bronchopulmonary dysplasia, n (%)	74 (22.1)	12 (17.4)	32 (16.5)	47 (16.7)	.269
Intraventricular hemorrhage, n (%)	90 (26.2)	16(22.5)	39 (19.3)	60 (21.1)	.245
Necrotizing enterocolitis, n (%)	32 (9.3)	2 (2.8)	23 (11.4)	24 (8.5)	.162
Patent ductus arteriosus, n (%)	58 (16.9)	15 (21.1)	46 (22.8)	57 (20.1)	.389
Periventricular leukomalacia, n (%)	12 (3.5)	0 (0.0)	3(1.5)	7 (2.5)	.299
Retinopathy of prematurity, n (%)	42 (12.2)	10(14.1)	20 (9.9)	26 (9.2)	.479
Median days in NICU (IQR)	30.0 (52.8)	33.0 (35.5)	36.0 (28.0)	31.0 (38.0)	.130

FVT, fetal vascular thrombosis; HELLP, hemolysis, elevated liver enzymes, low platelet count; IQR, interquartile range; MVM, maternal vascular malperfusion; NICU, neonatal intensive care unit; PPROM, preterm premature rupture of membranes; PTB, preterm birth.

^aCategorical variables were compared across groups by chi-square and Fisher exact tests. Days in NICU were compared across groups using Kruskal-Wallis test;

^bDenotes nominal significance at P<.05;

^cDenotes statistical significance after adjusting for multiple pregnancy (0.05/8 outcomes=0.006) and neonatal outcomes (0.05/10=0.005);

^dData were missing for hypertensive disorders of pregnancy (n=2), delivery method (n=3), cesarean delivery (n=27), smallness for gestational age (n=21), severe neonatal morbidity (n=21), respiratory distress (n=21), bronchopulmonary dysplasia (n=21), and median days in NICU (n=136);

^eSevere neonatal morbidity is a composite outcome of respiratory distress, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, patent ductus arteriosus, periventricular leukomalacia, and retinopathy of prematurity.

TABLE 3.

Pregnancy and neonatal outcomes based on placental pathology in late preterm births (n=3362)^a,b,c,d

Clinical outcomes	Acute inflammation (n=401)	FVT with hemorrhage (n=299)	Low-risk pathology (n=2088)	MVM (n=574)	Pvalue
Pregnancy outcomes
Diabetes mellitus, n (%)					.365
None	345 (86.0)	247 (82.6)	1762 (84.4)	497 (86.6)
Preexisting	39 (9.7)	29 (9.7)	203 (9.7)	43 (7.5)
Gestational	17(4.2)	23 (7.7)	123 (5.9)	34 (5.9)
Hypertensive disorders, n (%)					<.001c
No hypertensive disorders	335 (84.0)	191 (63.9)	1621 (77.8)	243 (42.4)
Gestational hypertension	11 (2.8)	11 (3.7)	77 (3.7)	26 (4.5)
Preeclampsia, HELLP syndrome, eclampsia	53 (13.3)	97 (32.4)	386 (18.5)	304 (53.1)
Cervical shortening, n (%)	4(1.0)	2(0.7)	4 (0.2)	3 (0.5)	.033b
Clinical chorioamnionitis, n (%)	35 (8.7)	1 (0.3)	30 (1.4)	3 (0.5)	<.001c
PPROM, n (%)	175 (43.6)	62 (20.7)	631 (30.2)	120 (20.9)	<.001c
Delivery method, n (%)					<.001c
Indicated	100 (25.0)	167(55.9)	807 (38.6)	372 (64.9)
Spontaneous	300 (75.0)	132 (44.1)	1281 (61.4)	201 (35.1)
Cesarean delivery, n (%)	91 (23.2)	138(47.3)	700 (34.2)	270 (47.7)	<.001c
Male fetal sex, n (%)	219(54.6)	141 (47.2)	1151 (55.1)	310(54.0)	.081
Neonatal outcomes
Smallness for gestational age, n (%)	58 (14.5)	54 (18.1)	228 (11.0)	241 (42.1)	<.001c
Severe neonatal morbidity, n (%)e	44 (11.3)	58 (19.9)	263 (12.9)	91 (16.5)	.001c
Respiratory distress, n (%)	33 (8.5)	44 (15.1)	219(10.8)	60 (10.9)	.053
Bronchopulmonary Dysplasia, n (%)	0 (0.0)	0 (0.0)	5 (0.3)	4(0.7)	.190
Intraventricular hemorrhage, n (%)	14(3.5)	8(2.7)	45 (2.2)	26 (4.5)	.016b
Necrotizing enterocolitis, n (%)	2 (0.5)	4(1.3)	10(0.5)	9(1.6)	.026b
Patent ductus arteriosus, n (%)	3 (0.8)	6 (2.0)	24 (1.2)	11 (1.9)	.229
Periventricular leukomalacia, n (%)	1 (0.3)	1 (0.3)	4 (0.2)	1 (0.2)	.793
Retinopathy of prematurity, n (%)	0 (0.0)	2 (0.7)	1 (0.0)	5 (0.9)	.002
Median days in NICU (IQR), n (%)	6.0 (13.8)	2.0 (12.0)	1.0 (9.0)	9.0 (18.0)	<.001

FVT, fetal vascular thrombosis; HELLP, hemolysis, elevated liver enzymes, low platelet count; IQR, interquartile range; MVM, maternal vascular malperfusion; NICU, neonatal intensive care unit; PPROM, preterm premature rupture of membranes; PTB, preterm birth.

^aCategorical variables were compared across groups by chi-square and Fisher exact tests. Days in NICU were compared across groups using Kruskal-Wallis test;

^bDenotes nominal significance at P<.05;

^cDenotes statistical significance after adjusting for multiple pregnancy (0.05/8 outcomes=0.006) and neonatal outcomes (0.05/10=0.005);

^dData were missing for hypertensive disorders of pregnancy (n=7), delivery method (n=2), cesarean delivery (n=63), smallness for gestational age (n=13), severe neonatal morbidity (n=95), respiratory distress (n=95), bronchopulmonary dysplasia (n=95), and median days in NICU (n=404);

^eSevere neonatal morbidity is a composite outcome of respiratory distress, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, patent ductus arteriosus, periventricular leukomalacia, and retinopathy of prematurity.

Layden et al. Latent class analysis of early and late preterm births. Am J Obstet Gynecol 2022.

Comment

Principal findings

Early PTBs were classified as having acute inflammation, MVM, FVT with hemorrhage, and features of MVM and chorioamnionitis. In contrast, over half of late PTBs had minimal placental pathology, with the remaining late PTBs having acute inflammation, MVM, and FVT with hemorrhage. Prepregnancy BMI was associated with an increased likelihood of MVM in early but not late PTB, and this association was not modified by clinical presentation of PTB (spontaneous or indicated). MVM and FVT with hemorrhage were associated with greater neonatal morbidity than the other latent classes in early and late PTBs.

Results in the context of what is known

Among early PTBs, acute inflammation was the most frequent placental latent class, which was perhaps reflective of intrauterine infection. Infection causes 25% to 40% of PTBs and risk of infection increases with earlier delivery.^37,45 Acute inflammation had the highest prevalence of clinical chorioamnionitis, spontaneous labor, and PPROM relative to the other classes. In exploratory analyses, no differences in placental latent classes were observed by PPROM status in early spontaneous PTBs to suggest differing pathophysiology. MVM and FVT with hemorrhage were 2 other classes in early PTBs. Placental features in the MVM latent class (decidual vasculopathy, villous infarct, placental hypoplasia, advanced villous maturation) aligned with the Amsterdam criteria.^46,47 Placental features of FVT with hemorrhage (including fetal vascular thrombosis, intervillous thrombus, villous infarct, acute chorioamnionitis) did not align with the Amsterdam criteria, but perhaps reflect PTBs with endothelial injury of placental vessels caused by inflammation.⁴⁸ A third of early PTBs had cooccurring chorioamnionitis and malperfusion (advanced villous maturation and placental hypoplasia). This aligns with findings on the same cohort of PTBs that a priori measured the cooccurrence of MVM with intrauterine infection¹³ and findings from a cohort of 109 PTBs (<34 weeks).⁴⁹ Vascular impairment from maternal morbidity may predispose the placenta to infection, but future studies are warranted.¹³

Most late PTBs had low risk of any placental pathology. A study from the same cohort found that 31% of late PTBs (34—36 weeks) had no placental histopathology findings.¹³ Another study found that 30% of PTBs had no severe maternal, fetal, or placental conditions (eg, preeclampsia or fetal growth restriction).⁵⁰ Inaccurate gestational dating of term births as PTBs is unlikely to explain our findings given that excluding pregnancies at 36 weeks did not change the latent classes. It is also unlikely that late PTBs were attributable to iatrogenic causes by a healthcare provider because 61% of the low-risk pathology latent class experienced spontaneous labor. Late PTBs may occur for reasons not mediated by the placenta (eg, maternal or fetal conditions) or from placental dysfunction at a molecular level not detected by placental histopathology.

Increasing prepregnancy BMI was associated with a higher likelihood of MVM in early PTB, but no placental pathology in late PTB. MVM had the highest prevalence of hypertensive disorders of pregnancy in early PTBs. Obesity may predispose women to early PTB through vascular impairment, and our findings align with studies that have reported obesity to be a risk factor for early but not late PTB.^2,51 Higher gestational weight gain was also associated with MVM in exploratory analyses of early PTBs. Other adiposity measures are worth investigating.

MVM and FVT with hemorrhage were associated with greater neonatal morbidity compared with the other latent classes in early and late PTBs. Previous literature has shown MVM is associated with fetal growth restriction, neonatal thrombocytopenia, and intra- ventricular hemorrhage,^{13,47,52–54} and fetal thrombotic vasculopathy is associated with fetal demise, growth restriction, and cardiac anomalies.^32,55

Research and clinical implications

LCA can aid pathologists in refining diagnostic criteria for placental pathology set by the Amsterdam Placental Workshop Group. The cooccurrence of MVM with acute inflammation may reflect understudied inflammatory pathology in women with underlying vascular impairment. Alternatively, placental hypoplasia and advanced villous maturation were present across all latent classes of early PTBs, possibly indicating less precise measures of MVM.

Current preterm interventions (cerclage, progesterone) are effective in a subset of pregnancies. Quantifying associations between maternal factors and placental subtypes of PTBs may inform management of other high-risk subgroups of pregnancies. We found BMI to be associated with early PTBs with MVM. Future studies could also assess risk factors (autoimmune disorders, infection) predictive of PTBs with acute placental inflammation. Risk factors aligning with specific placental mediators of PTB may be targetable for intervention. Classifying PTBs by placental subtypes may also be more prognostic of neonatal morbidity than other PTB classifications. MVM and FVT with hemorrhage were associated with neonatal morbidity.

LCA offers an approach to predict risk of PTB and other syndromes (eg, stillbirth) using clinical data collected in early pregnancy. Studies have predicted risk of cardiovascular events and cancer on the basis of LCA of self-reported depressive symptoms⁵⁶ and metabolic biomarkers, respectively.⁵⁷

Strengths and limitations

Strengths of this study include the generalizability of our findings to most PTBs in Pittsburgh, Pennsylvania, given that placental evaluations were available in 89% of all singleton PTBs delivered at UPMC Magee-Womens Hospital. Placental histopathology was collected using a standardized protocol. Groupings of placental features were determined by a data-driven method to minimize bias from a priori knowledge.

Study limitations included an inability to evaluate chronicity (eg, chronic chorioamnionitis) and severity of placental features because these aspects were not validated for automated extraction,²⁹ and may have variable detection. Except for some placental features of inflammation and MVM, reporting agreement of other placental features was not measured and may vary across pathologists.^13,14,33,58 Further, agreement between pathology reports and manual review of placental features (advanced villous maturation) commonly reported at earlier gestation may be impacted by lack of blinding to gestational age; the pathologist was blinded to all other clinical data. Another limitation was that 42% of deliveries were missing data on prepregnancy BMI. However, the direction of associations between BMI and likelihood of latent classes were consistent across complete- case and multiple-imputation analyses. Prepregnancy BMI was self-reported, although BMI misclassification did not impact findings in a previous study of this cohort.⁵⁹ SGA based on birthweights was a proxy for fetal growth restriction because of missing fetal ultrasound data. Lastly, only 37% of term births had histopathology evaluations, and term pregnancies with complications are oversampled, making comparisons to PTBs unfeasible.

Conclusions

LCA of placental features offers an empirical approach to group PTBs into classes possibly reflective of etiology. We found an understudied cluster of early PTBs with features of inflammation and MVM and report that early PTBs with MVM are associated with worse neonatal outcomes compared with PTBs with other pathology. Further, we report maternal obesity to be associated with early PTBs with MVM. The translation of these placental phenotypes to risk factors measurable in early pregnancy may inform earlier identification of PTB risk and opportunities for intervention.

AJOG at a Glance.

Why was this study conducted?

To classify early and late preterm births by pathophysiology using latent class analysis of placental histopathologic data and to determine if latent classes were associated with prepregnancy obesity and neonatal morbidity.

Key findings

Early preterm births grouped into 2 known placental phenotypes: acute inflammation and maternal vascular malperfusion, and 2 novel phenotypes: maternal malperfusion with chorioamnionitis and fetal vascular thrombosis with hemorrhage. Half of late preterm births had no evident predominant placental pathology. From 20 to 50 kg/m², prepregnancy body mass index doubled the probability of maternal vascular malperfusion in early but not late preterm births. Smallness for gestational age and severe neonatal morbidity were most prevalent among deliveries with placental malperfusion.

What does this add to what is known?

A novel approach to classify preterm births into subgroups with distinct placental etiologies and risk factors like obesity.