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• When is birth optimal for women with chronic or gestational hypertension at term?. • Planned early term birth may reduce maternal morbidity and pre-eclampsia. • Ongoing expectant care may reduce neonatal morbidity. • The WILL trial is designed to resolve these uncertainties. To address optimal timing of birth for women with chronic or gestational hypertension who reach term and remain well. Pragmatic, non-masked randomised trial. Inclusion: maternal age ≥16 years, chronic or gestational hypertension, singleton pregnancy, live fetus, 36+0–37+6 weeks' gestation, and able to give documented informed consent. Exclusion: contraindication to either trial arm (e.g., pre-eclampsia or another indication for birth at term), blood pressure (BP) ≥ 160/110 mmHg until controlled, major fetal anomaly anticipated to require neonatal care unit admission, or participation in another timing of birth trial. Randomisation (1:1 ratio, minimised for key prognostic variables: site, hypertension type, and prior Caesarean) to 'planned early term birth at 38+0-3 weeks' or 'usual care at term' (revised from 'expectant care until at least 40+0 weeks', Aug 2022). Maternal co-primary: composite of 'poor maternal outcome' (severe hypertension, maternal death, or maternal morbidity). Neonatal co-primary: neonatal care unit admission for ≥4 h. Each co-primary is measured until primary hospital discharge or 28 days post-birth (whichever is earlier). Key secondary: Caesarean birth. Sample of 1080 participants (540/arm) will detect an 8% reduction in the maternal co-primary (90% power, superiority hypothesis), and give 94% power for a between-group non-inferiority margin of difference of 9% in the neonatal co-primary. Analysis will be by intention-to-treat. Ethics approval has been obtained (NHS Health Research Authority London Fulham Research Ethics Committee, 18/LO/2033). The study will provide data for women to make informed choices about their care and allow health systems to plan services. [ABSTRACT FROM AUTHOR]

Background: Prevalence statistics for pregnancy complications identified through screening such as gestational diabetes usually assume universal screening. However, rates of screening completion in pregnancy are not available in many birth registries or hospital databases. We validated screening-test completion by comparing public insurance laboratory and radiology billing records with medical records at three hospitals in British Columbia, Canada. Methods: We abstracted a random sample of 140 delivery medical records (2014–2019), and successfully linked 127 to valid provincial insurance billings and maternal–newborn registry data. We compared billing records for gestational diabetes screening, any ultrasound before 14 weeks gestational age, and Group B streptococcus screening during each pregnancy to the gold standard of medical records by calculating sensitivity and specificity, positive predictive value, negative predictive value, and prevalence with 95% confidence intervals (CIs). Results: Gestational diabetes screening (screened vs. unscreened) in billing records had a high sensitivity (98% [95% CI = 93, 100]) and specificity (>99% [95% CI = 86, 100]). The use of specific glucose screening approaches (two-step vs. one-step) were also well characterized by billing data. Other tests showed high sensitivity (ultrasound 97% [95% CI = 92, 99]; Group B streptococcus 96% [95% CI = 89, 99]) but lower negative predictive values (ultrasound 64% [95% CI = 33, 99]; Group B streptococcus 70% [95% CI = 40, 89]). Lower negative predictive values were due to the high prevalence of these screening tests in our sample. Conclusions: Laboratory and radiology insurance billing codes accurately identified those who completed routine antenatal screening tests with relatively low false-positive rates. [ABSTRACT FROM AUTHOR]

Background: Associations between pregnancy weight gain and adverse outcomes may be spurious owing to confounding by factors not typically measured in cohort studies. We determined the extent to which the addition of detailed behavioral, psychosocial, and environmental measurements to commonly available covariates improved control of confounding.Methods: We used data from a prospective US pregnancy cohort study (2010-2013, n = 8978). We calculated two propensity scores for low and high pregnancy weight gain (vs. adequate gain) using 11 standard confounders (e.g., age and education). We examined the balance of characteristics between weight gain groups before and after propensity score matching. We used negative binomial regression to estimate the association between weight gain and small- and large-for-gestational-age birth, preterm birth, and unplanned cesarean delivery, controlling for propensity score. To this model, we then added 17 detailed behavioral, psychosocial, and environmental measurements ("fully adjusted"). We calculated the risk ratio owing to confounding as the ratio of the standard confounder-adjusted risk ratio to the fully adjusted risk ratio.Results: There were minimal imbalances between weight gain groups in detailed measures after matching for a propensity score of standard covariates. Accordingly, the inclusion of detailed covariates had minimal impact on estimated associations between low or high pregnancy weight gain and adverse pregnancy outcomes: risk ratios owing to confounding were null for all outcomes (e.g., 1.1 [95% CI = 1.0, 1.1] for low weight gain and preterm birth).Conclusions: Adjustment for detailed behavioral, psychosocial, and environmental measurements had minimal impact on estimated associations between pregnancy weight gain and adverse perinatal outcomes. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes might be more common in twin versus singleton pregnancies, yet the reasons for this are unclear. We evaluated the extent to which this relationship is explained by higher mid-pregnancy weight gain within normal weight and overweight pre-pregnancy body mass index (BMI) strata.Methods: We analyzed serial weights and glucose screening and diagnostic data abstracted from medical charts for twin (n = 1397) and singleton (n = 3117) pregnancies with normal or overweight pre-pregnancy BMI delivered from 1998 to 2013 at Magee-Womens Hospital in Pennsylvania. We used causal mediation analyses to estimate the total effect of twin versus singleton pregnancy on gestational diabetes, as well as those mediated (natural indirect effect) and not mediated (natural and controlled direct effects) by pathways involving mid-pregnancy weight gain.Results: Odds of gestational diabetes were higher among twin pregnancies [odds ratios (ORs) for total effect = 2.83 (95% CI = 1.54, 5.19) for normal weight and 2.09 (95% CI = 1.16, 3.75) for overweight pre pregnancy BMI], yet there was limited evidence that this relationship was mediated by mid-pregnancy weight gain [ORs for natural indirect effect = 1.21 (95% CI = 0.90, 1.24) for normal weight and 1.06 (95% CI = 0.92, 1.21) for overweight pre-pregnancy BMI] and more evidence of mediation via other pathways [ORs for natural direct effect = 2.34 (95% CI = 1.24, 4.40) for normal weight and 1.97 (95% CI = 1.08, 3.60) for overweight pre-pregnancy BMI].Conclusions: While twin pregnancies with normal weight or overweight pre-pregnancy BMI experienced higher odds of gestational diabetes versus singletons, most of this effect was explained by pathways not involving mid-pregnancy weight gain. [ABSTRACT FROM AUTHOR]

Background: Fetal growth restriction is commonly defined using small-for-gestational-age (SGA) birth (birthweight <10th percentile) as a proxy, but this approach is problematic because most SGA infants are small but healthy. In this proof-of-concept study, we sought to develop a new approach for identifying fetal growth restriction at birth that combines information on multiple, imperfect measures of fetal growth restriction in a probabilistic manner.Methods: We combined information on birthweight, placental weight, placental malperfusion lesions, maternal disease, and fetal acidemia using latent profile analysis to classify fetal growth in births at the Royal Victoria Hospital in Montreal, Canada, 2001-2009. We examined the clinical characteristics and health outcomes of infants classified as growth-restricted and non-growth-restricted by our model, and among the subgroup of growth-restricted infants who had a birthweight ≥10th percentile (i.e., would have been missed by the conventional SGA proxy).Results: Among 26,077 births, 345 (1.3%) were classified as growth-restricted by our latent profile model. Growth-restricted infants were more likely than non-growth-restricted infants to have an Apgar score <7 (10 vs. 2%), have hypoglycemia at birth (17 vs. 3%), require neonatal intensive care unit admission (NICU, 59 vs. 6%), die in the perinatal period (3.8 vs. 0.2%), and require an emergency cesarean delivery (42 vs. 15%). Risks remained elevated in growth-restricted infants who were not SGA, suggesting our model identified at-risk infants not detected using the SGA proxy.Conclusions: Latent profile analysis is a promising strategy for classifying growth restriction at birth in fetal growth restriction research. [ABSTRACT FROM AUTHOR]

Background: In perinatal epidemiology, the development of risk prediction models is complicated by parity; how repeat pregnancies influence the predictive accuracy of models that include obstetrical history is unclear.Methods: To assess the influence of repeat pregnancies on the association between predictors and the outcomes, as well as the influence of ignoring the nonindependence between pregnancies, we created four analytical cohorts using the Clinical Practice Research Datalink. The cohorts included (1) first deliveries, (2) a random sample of one delivery per woman, (3) all eligible deliveries per woman, and (4) all eligible deliveries and censoring of follow-up at subsequent pregnancies. Using Plasmode simulations, we varied the predictor-outcome association across cohorts.Results: We found minimal differences in the relative contribution of predictors to the overall predictions and the discriminative accuracy of models in the cohort of randomly sampled deliveries versus the all deliveries cohort (C-statistic: 0.62 vs. 0.63; Nagelkerke's R2: 0.03 for both). Accounting for clustering and censoring upon subsequent pregnancies also had negligible influence on model performance. We found important differences in model performance between the models developed in the cohort of first deliveries and the random sample of deliveries.Conclusions: In our study, a model including first deliveries had the best predictive accuracy but was not generalizable to women of varying parities. Moreover, including repeat pregnancies did not improve the predictive accuracy of the models. Multiple models may be needed to improve the transportability and accuracy of prediction models when the outcome of interest is influenced by parity. [ABSTRACT FROM AUTHOR]

Background: Fetal growth standards (prescriptive charts derived from low-risk pregnancies) are theoretically better tools to monitor fetal growth than conventional references. We examined how modifying chart inclusion criteria influenced the resulting curves.Methods: We summarized estimated fetal weight (EFW) distributions from a hospital's routine 32-week ultrasound in all nonanomalous singleton fetuses (reference) and in those without maternal-fetal conditions affecting fetal growth (standard). We calculated EFWs for the 3rd, 5th, 10th, and 50th percentiles, and the proportion of fetuses each chart classified as small for gestational age.Results: Of 2309 fetuses in our reference, 690 (30%) met the standard's inclusion criteria. There were no meaningful differences between the EFW distributions of the reference and standard curves (50th percentile: 1989 g reference vs. 1968 g standard; 10th percentile: 1711 g reference vs. 1710 g standard), or the proportion of small for gestational age fetuses (both 9.9%).Conclusions: In our study, there was little practical difference between a fetal growth reference and standard for detecting small infants. [ABSTRACT FROM AUTHOR]

Background: Blood transfusion is frequently used as an indicator of severe maternal morbidity during pregnancy. However, few studies have examined its validity in population perinatal databases.Methods: We linked a perinatal database from British Columbia, Canada, with the province's Central Transfusion Registry for 2004-2015 deliveries. Using the Central Transfusion Registry records for red blood cell transfusion as the gold standard, we calculated the sensitivity, specificity, positive predictive value, and negative predictive value of the perinatal database variable for red blood cell transfusion, overall and by transfusion risk factor status. We used multivariable logistic regression to examine whether outcome misclassification altered the odds ratios for different transfusion risk factors.Results: Among 473,688 deliveries, 4,033 (8.5 per 1,000) had a red blood cell transfusion according to the Central Transfusion Registry. The sensitivity of the perinatal database transfusion variable was 72.3 [95% confidence interval (CI) = 72.2, 72.4]. Sensitivity differed according to the presence of many transfusion risk factors (e.g., 84.9% vs. 72.2% in deliveries with versus without uterine rupture). Odds ratios associated with some transfusion risk factors were exaggerated when the perinatal database transfusion variable was used to define the outcome instead of the Central Transfusion Registry variable, but 95% confidence intervals for these estimates overlapped.Conclusion: Blood transfusion was documented with reasonable sensitivity in this large population perinatal database. However, validity varied according to risk factor status. Our findings enable researchers to better account for outcome misclassification in studies of obstetrical transfusion risk factors. [ABSTRACT FROM AUTHOR]

Background: Observational cohort studies have consistently shown that maternal weight gain in pregnancy is positively associated with fetal size, but it is unknown whether the association is causal. This study investigated the effect of pregnancy weight gain on fetal growth using a sibling comparison design to control for unmeasured confounding by genetic and shared environmental factors.Methods: Our study population included 44,457 infants (21,680 women) with electronic medical records in the Stockholm-Gotland Obstetrical Database, 2008-2014. We standardized pregnancy weight gain into gestational age-specific z-scores. Fetal size was classified as birthweight (gram), and as small- and large-for-gestational-age birth (birthweight <10th or >90th percentiles, respectively). Our sibling comparison analyses used multivariable linear fixed effects models for birthweight and hybrid logistic fixed effects models for small- and large-for-gestational-age birth (SGA and LGA). We repeated analyses using conventional (unmatched) regression models.Results: Sibling comparison analyses showed a clinically meaningful association between weight gain and fetal size (e.g., adjusted difference of +89 g birthweight [95% CI = 82, 95 g]; adjusted risk ratios [aRR] for SGA of 0.80 [95% CI = 0.75, 0.86] per 1 z-score increase in weight gain for a woman of body mass index [BMI] = 25). These findings were consistent across the range of BMI. Estimates were only modestly attenuated compared with conventional approach (+97 g [95% CI = 92, 102 g], aRR for SGA of 0.70 [95% CI = 0.67, 0.73] per 1 z-score increase in weight gain).Conclusion: The positive association between pregnancy weight gain and fetal size we found using a sibling comparison design suggests that this relation has minimal confounding by familial factors that remain constant between pregnancies. [ABSTRACT FROM AUTHOR]

The fullPIERS model is a risk prediction model developed to predict adverse maternal outcomes within 48 h for women admitted with pre-eclampsia. External validation of the model is required before implementation for clinical use. We assessed the temporal and external validity of the fullPIERS model in high income settings using five cohorts collected between 2003 and 2016, from tertiary hospitals in Canada, the United States of America, Finland and the United Kingdom. The cohorts were grouped into three datasets for assessing the primary external, and temporal validity, and broader transportability of the model. The predicted risks of developing an adverse maternal outcome were calculated using the model equation and model performance was evaluated based on discrimination, calibration, and stratification. Our study included a total of 2429 women, with an adverse maternal outcome rate of 6.7%, 6.6%, and 7.0% in the primary external, temporal, and combined (broader) validation cohorts, respectively. The model had good discrimination in all datasets: 0.81 (95%CI 0.75-0.86), 0.82 (95%CI 0.76-0.87), and 0.75 (95%CI 0.71-0.80) for the primary external, temporal, and broader validation datasets, respectively. Calibration was best for the temporal cohort but poor in the broader validation dataset. The likelihood ratios estimated to rule in adverse maternal outcomes were high at a cut-off of ≥30% in all datasets. The fullPIERS model is temporally and externally valid and will be useful in the management of women with pre-eclampsia in high income settings although model recalibration is required to improve performance, specifically in the broader healthcare settings. [ABSTRACT FROM AUTHOR]

Objective: To investigate the association between early-pregnancy weight gain and risk of preeclampsia to inform pregnancy weight gain recommendations.Study Design: We performed a case-cohort study using a hospital database including 80,812 singleton deliveries from Magee-Womens Hospital, Pittsburgh, Pennsylvania (1998-2011). In each of 6 prepregnancy body mass index (BMI) groups, we abstracted serial antenatal weight measurements from the records of up to 339 preeclampsia cases and 1254 randomly selected pregnancies. Early gestational weight gain (16-19 weeks' gestation) was standardized for gestational duration using BMI-specific z-score charts. Multivariable log-binomial regression was used to assess the association between weight gain z-score and risk of preeclampsia. We determined the impact of preeclampsia misclassification using probabilistic bias analysis.Main Outcome Measure: Risk of preeclampsia.Results: For normal weight women, there was a steady increase in preeclampsia risk with increasing early gestational weight gain z-score. For example, compared with a weight gain of 1.2 kg (z-score = -1 SD), a 7.2-kg weight gain (z-score = +1 SD) at 16 weeks was associated with 1.3 (0.50, 2.2) excess preeclampsia cases per 100 deliveries. Weight loss at 16-19 weeks among grade 2 or 3 obese women was associated with a reduced risk of preeclampsia. Associations were null among overweight and grade 1 obese women. The bias analysis supported the validity of the conventional analysis.Conclusions: Early-pregnancy weight gain may be associated with preeclampsia in some BMI groups. Future revisions of pregnancy weight gain recommendations should account for preeclampsia risks from this and additional studies. [ABSTRACT FROM AUTHOR]

Weight gain in early pregnancy may influence a woman's risk of developing preeclampsia. However, the consequences of weight gain throughout pregnancy up to the diagnosis of preeclampsia are unknown. The aim of this study was to determine whether pregnancy weight gain before the diagnosis of preeclampsia is associated with increased risks of preeclampsia (overall and by preeclampsia subtype). The study population included nulliparous pregnant women in the Swedish counties of Gotland and Stockholm, 2008 to 2013, stratified by early pregnancy body mass index category. Electronic medical records were linked with population inpatient and outpatient records to establish date of preeclampsia diagnosis (classified as any, early preterm <34 weeks, late preterm 34-36 weeks, or term ≥37 weeks). Antenatal weight gain measurements were standardized into gestational age-specific z scores. Among 62 705 nulliparous women, 2770 (4.4%) developed preeclampsia. Odds of preeclampsia increased by ≈60% with every 1 z score increase in pregnancy weight gain among normal weight and overweight women and by 20% among obese women. High pregnancy weight gain was more strongly associated with term preeclampsia than early preterm preeclampsia (eg, 64% versus 43% increased odds per 1 z score difference in weight gain in normal weight women, and 30% versus 0% in obese women, respectively). By 25 weeks, the weight gain of women who subsequently developed preeclampsia was significantly higher than women who did not (eg, 0.43 kg in normal weight women). In conclusion, high pregnancy weight gain before diagnosis increases the risk of preeclampsia in nulliparous women and is more strongly associated with later-onset preeclampsia than early-onset preeclampsia. [ABSTRACT FROM AUTHOR]

Background: First deliveries in women older than 35, 40, or 45 years are at increased risk for adverse pregnancy outcomes compared with those in younger women. However, specific relationships between each additional year of maternal age and pregnancy risks remain unclear, and absolute risks at each maternal age are not known.Methods: Using a population-based cohort of nulliparous women in British Columbia, Canada, from 2004 to 2014 (n = 203,414), We examined relationships between maternal age (modeled flexibly to allow curvilinear shapes) and pregnancy outcomes using logistic regression. We plotted absolute predicted risks to display curves from age 20 to 50 estimated for two risk profiles: (1) population average values of all risk factors; (2) a low-risk profile without preexisting diabetes/hypertension, smoking, prior spontaneous/therapeutic abortion, diagnosed infertility, inadequate prenatal care, low income, rural residence, or obesity.Results: Risks of hypertensive disorders increased gradually until age 35, then accelerated. Risk of multiple gestations, major congenital anomalies, and maternal mortality or severe morbidity increased slowly until age 30, then accelerated. Cesarean delivery and gestational diabetes risks increased linearly with age. While indicated preterm delivery increased rapidly with maternal age, spontaneous preterm delivery did not. Stillbirth, neonatal mortality, and infant mortality had j-shaped relationships with maternal age, with nadirs near 30. Despite age-related increases, risks of severe outcomes remained low for women 35 and 40: < 1-2% for severe maternal morbidity and 5-7% for fetal-infant composite.Conclusions: This study provides risks for specific maternal ages to inform clinical counseling and public health messaging regarding the potential implications of delayed childbearing. [ABSTRACT FROM AUTHOR]

Early-onset preeclampsia is associated with severe maternal and perinatal complications. The fullPIERS model (Preeclampsia Integrated Estimate of Risk) showed both internal and external validities for predicting adverse maternal outcomes within 48 hours for women admitted with preeclampsia at any gestational age. This ability to recognize women at the highest risk of complications earlier could aid in preventing these adverse outcomes through improved management. Because the majority (≈70%) of the women in the model development had late-onset preeclampsia, we assessed the performance of the fullPIERS model in women with early-onset preeclampsia to determine whether it will be useful in this subgroup of women with preeclampsia. Three cohorts of women admitted with early-onset preeclampsia between 2012 and 2016, from tertiary hospitals in Canada, the Netherlands, and United Kingdom, were used. Using the published model equation, the probability of experiencing an adverse maternal outcome was calculated for each woman, and model performance was evaluated based on discrimination, calibration, and stratification. The total data set included 1388 women, with an adverse maternal outcome rate of 7.3% within 48 hours of admission. The model had good discrimination, with an area under the receiver operating characteristic curve of 0.80 (95% confidence interval, 0.75-0.86), and a calibration slope of 0.68. The estimated likelihood ratio at the predicted probability of ≥30% was 23.4 (95% confidence interval, 14.83-36.79), suggesting a strong evidence to rule in adverse maternal outcomes. The fullPIERS model will aid in identifying women admitted with early-onset preeclampsia in similar settings who are at the highest risk of adverse outcomes, thereby allowing timely and effective interventions. [ABSTRACT FROM AUTHOR]

Background: The hypertensive disorders of pregnancy are a leading cause of maternal and perinatal mortality and morbidity. The ability to predict these complications using simple tests could aid in management and improve outcomes. We aimed to systematically review studies that reported on potential predictors of adverse maternal outcomes among women with a hypertensive disorder of pregnancy.Methods: We searched MEDLINE, Embase and CINAHL (inception - December 2016) for studies of predictors of severe maternal complications among women with a hypertensive disorder of pregnancy. Studies were selected in a two-stage process by two independent reviewers, excluding those reporting only on adverse fetal outcomes. We extracted data on study and test(s) characteristics and outcomes. Accuracy of prediction was assessed using sensitivity, specificity, likelihood ratios and area under the receiver operating curve (AUROC). Strong evidence of prediction was taken to be a positive likelihood ratio >10 or a negative likelihood ratio <0.1, and for multivariable models, an AUROC ≥0.70. Bivariate random effects models were used to summarise performance when possible.Results: Of 32 studies included, 28 presented only model development and four examined external validation. Tests included symptoms and signs, laboratory tests and biomarkers. No single test was a strong independent predictor of outcome. The most promising prediction was with multivariable models, especially when oxygen saturation, or chest pain/dyspnea were included.Conclusion: Future studies should investigate combinations of tests in multivariable models (rather than single predictors) to improve identification of women at high risk of adverse outcomes in the setting of the hypertensive disorders of pregnancy. [ABSTRACT FROM AUTHOR]

The PlGF (placental growth factor) has been largely demonstrated to be associated with the diagnosis of the hypertensive disorders of pregnancy (HDPs); however, it is unclear how useful it is for the prognosis of the condition. Our objective was to provide a summary of important findings of its prognostic ability by systematically reviewing studies that examined the ability of the PlGF, either independently or combined with other factors, to predict maternal and fetal complications resulting from the HDPs. We included studies published before January 30, 2017, reporting on the use of the PlGF as a prognostic test for women with confirmed HDPs or suspected preeclampsia. Of the 220 abstracts identified through MEDLINE, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature), 17 studies were eligible for our review. Prognostic performance was evaluated by sensitivity, specificity, likelihood ratios, and area under the receiver operating characteristic curve. PlGF showed moderate-to-high evidence (likelihood ratios of ≥5 or ≤0.2 or area under the receiver operating characteristic curves ≥0.70) for identifying women at the highest risk of preterm delivery or neonatal outcomes (10/12 studies) but showed no clinically useful performance for the prediction of adverse maternal outcomes. PlGF may aid in the management of women with HDPs to avert fetal complications. Future studies should determine an optimum threshold for the marker to guide delivery and should examine whether its use for predicting adverse maternal outcomes in women with HDPs can be improved. [ABSTRACT FROM AUTHOR]

Background: Despite a call to study the effect of weight gain pattern on development of gestational diabetes mellitus, few studies have correctly adjusted for independent effects of gain after the first trimester. We used a conditional percentile approach to model the independent association between first and second trimester weight gain trajectories and development of gestational diabetes.Methods: We sampled women delivering singleton infants from 1998 to 2010 at Magee-Womens Hospital in Pittsburgh, PA, (n = 124,590) using a case-cohort design. We modeled weight gain trajectories in the first and second trimesters of pregnancy using conditional weight gain percentiles, and used multivariable logistic regression to assess independent associations of the trajectory with gestational diabetes. We studied associations separately by prepregnancy body mass index category.Results: The final cohort included 806 women with gestational diabetes and 4,819 randomly sampled women who delivered without gestational diabetes. In normal-weight women, every SD increase in weight gain in the first trimester above her predicted gain was associated with a 23% increased odds of gestational diabetes (95% confidence interval: 0.2%, 51%). Second trimester gain trajectory was not associated with gestational diabetes (odds ratio: 1.1, [95% confidence interval: 0.9, 1.3]) although the direction of effect was positive. This pattern was similar in obese class I and II but not in overweight and obese class III women.Conclusions: An upward weight gain trajectory in the first trimester was positively associated with gestational diabetes for women of most prepregnancy BMI categories. Second trimester weight gain trajectory was not associated with gestational diabetes for any group. [ABSTRACT FROM AUTHOR]

Background: Our objective was to estimate associations between gestational weight gain z scores and preterm birth, neonatal intensive care unit admission, large- and small-for-gestational age birth, and cesarean delivery among grades 1, 2, and 3 obese women.Methods: We included singleton infants born in Pennsylvania (2003-2011) to grade 1 (body mass index 30-34.9 kg/m, n = 148,335), grade 2 (35-39.9 kg/m, n = 72,032), or grade 3 (≥40 kg/m, n = 47,494) obese mothers. Total pregnancy weight gain (kg) was converted to gestational age-standardized z scores. Multivariable Poisson regression models stratified by obesity grade were used to estimate associations between z scores and outcomes. A probabilistic bias analysis, informed by an internal validation study, evaluated the impact of body mass index and weight gain misclassification.Results: Risks of adverse outcomes did not substantially vary within the range of z scores equivalent to 40-week weight gains of -4.3 to 9 kg for grade 1 obese, -8.2 to 5.6 kg for grade 2 obese, and -12 to -2.3 kg for grade 3 obese women. As gestational weight gain increased beyond these z score ranges, there were slight declines in risk of small-for-gestational age birth but rapid rises in cesarean delivery and large-for-gestational age birth. Risks of preterm birth and neonatal intensive care unit admission were weakly associated with weight gain. The bias analysis supported the validity of the conventional analysis.Conclusions: Gestational weight gain below national recommendations for obese mothers (5-9 kg) may not be adversely associated with fetal growth, gestational age at delivery, or mode of delivery. [ABSTRACT FROM AUTHOR]

Introduction: Discriminating between placentally-mediated fetal growth restriction and constitutionally-small fetuses is a challenge in obstetric practice. Placental growth factor (PlGF), measurable in the maternal circulation, may have this discriminatory capacity.Methods: Plasma PlGF was measured in women presenting with suspected fetal growth restriction (FGR; ultrasound fetal abdominal circumference <10th percentile for gestational age) at sites in Canada, New Zealand and the United Kingdom. When available, placenta tissue underwent histopathological examination for lesions indicating placental dysfunction, blinded to PlGF and clinical outcome. Lesions were evaluated according to pre-specified severity criteria and an overall severity grade was assigned (0-3, absent to severe). Low PlGF (concentration <5th percentile for gestational age) to identify placental FGR (severity grade≥2) was assessed and compared with routine parameters for fetal assessment. For all cases, the relationship between PlGF and the sampling-to-delivery interval was determined.Results: Low PlGF identified placental FGR with an area under the receiver-operator characteristic curve of 0.96 [95% CI 0.93-0.98], 98.2% [95% CI 90.5-99.9] sensitivity and 75.1% [95% CI 67.6-81.7] specificity. Negative and positive predictive values were 99.2% [95% CI 95.4-99.9] and 58.5% [95% CI 47.9-68.6], respectively. Low PlGF outperformed gestational age, abdominal circumference and umbilical artery resistance index in predicting placental FGR. Very low PlGF (<12 pg/mL) was associated with shorter sampling-to-delivery intervals than normal PlGF (13 vs. 29.5 days, P < 0.0001).Discussion: Low PlGF identifies small fetuses with significant underlying placental pathology and is a promising tool for antenatal discrimination of FGR from fetuses who are constitutionally-small. [ABSTRACT FROM AUTHOR]