BMC Pregnancy and Childbirth

ObjectivesTo determine temporal trends in the rates of preterm birth and its sub-types in Sweden and assess the contribution of known-risk factors. DesignA population-based register study. SettingSweden. Participants (Instead of patients or subjects)3,264,146 pregnancies registered in the Swedish Medical Birth Registry with information on pregnancy duration and onset of labour (1991 - 2021). Main outcome measuresThe primary outcomes were the overall, spontaneous and iatrogenic preterm birth rates between 1991 - 2021, stratified on singleton and multiple births, as well as for extremely preterm (<28 weeks, <196 days), very preterm (28-31 weeks, 196 - 224 days), moderately preterm (32 - 33 weeks, 224 - 238 days), and late preterm (34 - 36 weeks, 238 - 259 days) births. Using logistic regression models, we investigated whether maternal age at conception, use of artificial reproductive technologies, smoking, parity, and maternal continent of birth were associated with the observed trends. ResultsThe overall preterm birth rate was stable between 1991 - 2005 at 5.50% (95% CI: 5.37%, 5.63% in 1991) but decreased thereafter to 4.78% (95% CI: 4.66%, 4.91%) in 2021, a finding confined to spontaneous preterm births. The largest decline was observed in late preterm births, from 3.92% (95% CI: 3.80%, 4.05%) in 2005 to 3.52% (95% CI: 3.41%, 3.63%) in 2021. Moderately preterm birth also declined (0.70%, 95% CI: 0.65%, 0.76% in 2005 to 0.53%; 95% CI: 0.49%, 0.58% in 2021), whereas very-extremely preterm birth did not. Decreased spontaneous preterm birth rates were observed in women born in European, Asian and African countries, with largest decline observed in the latter (rate in 1991 = 2.65%, 95% CI: 1.74%, 3.86%; rate in 2021 = 1.72%, 95% CI: 1.42%, 2.07%). Adjusting for maternal and obstetric risk factors didnt alter these associations. ConclusionsWhile rates of preterm birth have been stable or increased globally, they have decreased in Sweden from 2006 - 2021, despite the lack of any nation-wide preventive strategy during this period. Understanding the reasons for this decline will provide useful strategies to make the decline a rule, rather than an exception.

Objective: To develop and validate a multivariable prediction model and clinically actionable risk score for vaginal birth after cesarean (VBAC) success using machine learning, and to integrate neonatal morbidity outcomes into a decision-analytic framework for trial of labor after cesarean (TOLAC) counseling. Methods: We performed a retrospective cohort study of 1,418 consecutive TOLAC cases at a single tertiary care center in California from 2019 through 2025. Multivariable logistic regression and four machine learning algorithms (logistic regression, random forest, gradient boosting, extreme gradient boosting) were trained using 5-fold stratified cross-validation. A cumulative risk score (negative 1 to 7 points) was constructed from independently significant predictors. Neonatal intensive care unit (NICU) admission rates and uterine rupture rates were evaluated across risk strata. Results: The overall VBAC rate was 76.7% (1,087/1,418). Penalized logistic regression achieved the highest cross-validated AUC (0.71, 95% CI 0.67 to 0.75). A parsimonious multivariable logistic model used for score derivation had an AUC of 0.70 (95% CI 0.67 to 0.73). Independent predictors of failed TOLAC included induction of labor (adjusted odds ratio [aOR] 1.93, 95% CI 1.48 to 2.52), hypertensive disorders (aOR 1.60, 95% CI 1.19 to 2.15), diabetes mellitus (aOR 1.71, 95% CI 1.19 to 2.47), obesity (body mass index [BMI] 30 or greater; aOR 1.46, 95% CI 1.11 to 1.90), maternal age of 40 years or older (aOR 1.49, 95% CI 0.89 to 2.50), and gestational age of 41 weeks or greater (aOR 2.22, 95% CI 1.40 to 3.52). Prior vaginal delivery was independently protective (aOR 0.37, 95% CI 0.28 to 0.48). The cumulative risk score stratified VBAC success from 89.1% (score negative 1) to 37.8% (score 4 or higher). NICU admission rates increased concordantly from 31.7 to 200.0 per 1,000 across risk strata negative 1 through 4 or higher (Spearman rho 0.94, P for trend = .005). Uterine rupture occurred in 28 cases (1.97%) and was associated with severe maternal morbidity (10.7% vs 0.7%; odds ratio 16.56, P < .001) but was not predicted by any antepartum risk factor. Exclusion of patients with risk scores of 3 or higher (11.3% of the cohort) improved overall VBAC success to 80.0% (P = .04) and reduced NICU rates to 66.0 per 1,000. Conclusion: A machine learning to derived cumulative risk score incorporating prior vaginal delivery as a protective factor identifies TOLAC candidates with poor VBAC prognosis and elevated neonatal morbidity, providing an evidence-based tool for individualized delivery counseling. Uterine rupture remains unpredictable by antepartum characteristics.

BackgroundPreterm premature rupture of membranes (PPROM) is a leading contributor of adverse perinatal outcomes, particularly in low-resource and conflict-affected settings. Despite its clinical importance, prospective evidence on its impact on composite adverse perinatal outcomes in northern Ethiopia remains limited. This study examined the impact of Preterm premature rupture of membranes on composite adverse perinatal outcomes and identified associated predictors among pregnant women in public hospitals of Tigray, Northern Ethiopia. MethodsA hospital-based prospective cohort study was conducted among 578 singleton pregnancies (288 with Preterm premature rupture of membranes and 290 without it at [&ge;]28 weeks of gestation. Participants were followed from admission to delivery and to the early neonatal period. The primary outcome was a Composite adverse perinatal outcome, and the main exposure variable was Preterm premature rupture of membranes (PPROM). Modified Poisson regression with robust variance estimation was used to estimate adjusted relative risks (ARRs) with 95% confidence intervals (CIs) and a significant level was declared at p<0.05. ResultsOverall, 33.4% of neonates experienced at least one composite adverse perinatal outcome. The incidence was substantially higher among the PPROM group compared with the non-PPROM group (59.4% vs. 7.6%). After adjustment, PPROM was strongly associated with composite adverse perinatal outcomes (ARR = 7.22, 95% CI: 4.73-11.03). Independent predictors included previous pregnancy-related infection (ARR = 1.54; 95% CI: 1.08-2.22), absence of iron-folate supplementation during pregnancy (ARR=1.63; 95% CI: 1.153-2.29), pelvic pain (ARR = 2.09; 95% CI: 1.05-4.15), and latency period of 1-3 days (ARR = 1.41; 95% CI: 1.10-1.81) compared to <24 hours. Induced labor was protective (ARR=0.58; 95% CI: 0 .422-0.800). ConclusionPPROM markedly increases the risk of composite adverse perinatal outcomes in this post-conflict, resource-constrained setting. The first 72 hours following membrane rupture represent a particularly vulnerable period. Strengthening antenatal care, nutritional supplementation, infection prevention, and timely obstetric intervention could reduce preventable neonatal morbidity and mortality in similar contexts.

Objective: To externally validate, at the national level, a cumulative risk score for vaginal birth after cesarean (VBAC) success and neonatal morbidity derived from single center data. Methods: We conducted a population based cohort study of all trial of labor after cesarean (TOLAC) attempts among term, singleton deliveries recorded in the Centers for Disease Control and Prevention natality files, 2020 to 2024 (N=477,693). The cumulative risk score (range - 1 to 7 points) incorporated body mass index (BMI) 30 or greater (+1), BMI 40 or greater (+1), induction of labor (IOL; +1), diabetes mellitus (+1), hypertensive disorder (+1), maternal age 40 years or older (+1), gestational age 41 weeks or greater (+1), and prior vaginal delivery (-1). VBAC success rates and neonatal intensive care unit (NICU) admission rates were evaluated across risk strata. Results: The overall VBAC rate was 73.3% (350,340/477,693). The cumulative risk score demonstrated a monotonic relationship with VBAC success: score -1, 90.5%; score 0, 76.4%; score 1, 69.4%; score 2, 62.2%; score 3, 55%; and score 4 or higher, 44.8%. NICU admission rates increased concordantly from 43.8 to 111.1 per 1,000 across strata. Prior vaginal delivery was the strongest individual predictor (VBAC 86.4% vs 62.5%). VBAC rates and TOLAC volume were stable across 2020 to 2024. Conclusion: The cumulative risk score derived from single center data was externally validated in a national cohort of 477,693 TOLAC attempts. The monotonic dose-response relationship between risk score and both VBAC success and NICU admission was confirmed, supporting the use of this score for individualized TOLAC counseling.

BackgroundBreech presentation which occurs in approximately 3% to 4% of all women at term, is a major concern for both pregnant mothers and their reproductive healthcare providers. This is because it is associated with increased adverse maternal and perinatal outcomes. ObjectiveTo describe the fetal and maternal outcomes of singleton breech deliveries at Moi Teaching and Referral Hospital (MTRH). MethodsThis was a cross-sectional descriptive study. The study participants were women with singleton breech deliveries at a gestation of 28 weeks or more. Hospital records indicated that very few breech deliveries occurred at the facility per year. Therefore, a census of all the eligible women with singleton breech deliveries was taken. A semi-structured interviewer-administered questionnaire was used for data collection. ResultsThere was a total of 11, 748 singleton deliveries at MTRH during the study period (30th August 2019 to 27th August 2020), of which 125 (1.06%) were singleton breech deliveries. Of these, 75 met the eligibility criteria to participate in the study whereby 65 (86.7%) gave birth through emergency caesarean section while 10 (13.3%) had emergency vaginal breech delivery. Most women (50.67%; n=38) delivered at a gestational age of between 38 - 40 weeks and 72 (96%) of the women enrolled had live births. Most (66.70%) newborns weighed 2500 - 3499grammes with 70 (93.3%) newborns having a 5-minute APGAR score of[&ge;]7. The majority (85.3%) of the newborns did not have birth complications however, 5 (6.7%) were admitted to the newborn unit due to birth asphyxia while 1 (1.3%) had delayed aftercoming head. The maternal complications noted were second- and third-degree perineal tears (5.3%), post-partum haemorrhage (4.0%) and anaesthetic complications (1.3%). ConclusionThis study noted that despite the MTRH breech delivery protocol recommendation for caesarean section for breech presentation, 13.3% of the women had vaginal breech deliveries. Birth complications (birth asphyxia, NBU admission and delayed aftercoming head) occurred in about 15% of the newborns regardless of the mode of delivery. Furthermore, 40% of these women sustained second- and third-degree perineal tears.

BackgroundPrior spontaneous preterm birth (sPTB) and short cervical length predict the occurrence of sPTB with low sensitivity, highlighting the need for better detectors of at-risk pregnancies. PreTRM(R) is a validated, biomarker-based sPTB predictor that we aimed to improve in this study by developing models that incorporate parity and key risk factors. MethodsA Model was developed and validated through retrospective analysis of a cohort of singleton pregnancies that resulted in live term or preterm birth (PTB). The Models ability to predict sPTB and PTB was assessed and its clinical utility compared to PreTRM. ResultsThe Model predicted sPTB with 77.1% sensitivity, 74.4% specificity, 21.4% positive predictive value (PPV) and 97.3% negative predictive value (NPV), an improvement over PreTRMs sensitivity (75.0%) and PPV (14.6%), and higher PPV than short cervix (16.2%). PTB was predicted by the Model with 76.8% sensitivity, 74.6% specificity, 31.6% PPV and 95.5% NPV. The Model predicted a neonatal hospital stay [&ge;]5 days with a significantly higher area under the receiver operating characteristic curve (AUC) than PreTRM associated with PTB (p = 0.001) and sPTB (p = 0.044). The Model also achieved significantly higher sensitivity than PreTRM at predicting a [&ge;]5 day hospital stay associated with PTB (p = 0.009) with improved sensitivity for sPTB, showing overall that the Model performs better than PreTRM in regard to clinical utility. ConclusionsThe Model achieved substantially higher performance than standard of care risk predictors, and an improvement in clinical utility over PreTRM, demonstrating the robustness of the Model as a PTB predictor.

Background: Despite significant advancements in obstetric care, the incidence of preeclampsia remains a substantial public health challenge, and effective strategies to prevent the disease progression remain limited, particularly in low-resource settings. N-acetylcysteine (NAC), an antioxidant and glutathione precursor, has demonstrated anti-inflammatory and vasodilatory effects, making it a promising candidate for repurposing. However, robust evidence from well-powered randomized controlled trials is lacking. Objective: This study will evaluate the impact of NAC on the time-to-disease progression in pregnant women with early-onset preeclampsia in Lagos, Nigeria. Methods: This is the study protocol for a proof-of-concept, double-blind, randomized, controlled trial to be conducted between April 2026 to July 2028 at the maternity units of the two teaching hospitals in Lagos, Nigeria. At baseline, n=153 sexually active women aged 18 years or older diagnosed with early-onset preeclampsia at 24 to 34 weeks gestation will be randomised to receive either daily oral tablet containing 600 mg of NAC or a placebo tablet that is matched for appearance and the dosing regimen in addition to standard antenatal care from diagnosis (randomisation) until either 34 weeks gestation or delivery, whichever comes first. The primary endpoint is the time-to-progression (in days) of early-onset preeclampsia to severe disease. The data analysis will be conducted on an intention-to-treat basis. Kaplan-Meier estimates with a Log-rank test will be used to calculate and compare the time-to-disease progression for the treatment groups, while Cox proportional hazard models with a backwards conditional method will be used to compare the primary endpoint between the treatment arms while adjusting for other covariates for precision using hazard ratios (HRs) and 95% confidence intervals (95%CIs). Subgroup analyses will also be performed to assess the differential effects of significant covariates on the impact of NAC on disease progression. Statistical significance will be reported as P<0.05. Discussion: This study will evaluate the efficacy of daily oral NAC compared to placebo in treating pregnant women with early-onset preeclampsia. If proven effective, NAC could offer a safe, affordable, and scalable intervention to reduce the burden of preeclampsia, particularly in resource-constrained settings.

BackgroundPlacental dysfunction remains a leading cause of stillbirth and neonatal morbidity, yet current monitoring tools provide only indirect and intermittent measures of fetoplacental wellbeing. Near-infrared spectroscopy (NIRS) offers non-invasive, continuous monitoring of tissue oxygenation and metabolism. ObjectivesTo develop a wearable NIRS system for placental monitoring (FetalSenseM v1 - FSM v1), investigate optical markers of placental oxygenation and metabolism in a population at high risk of adverse pregnancy outcomes such as stillbirth, and to apply machine learning analysis to develop a model for pregnancy outcome prediction. Study designIn this prospective observational study, women with high-risk singleton pregnancies underwent antenatal placental NIRS monitoring for over 40 minutes. FSM v1 incorporates dual-source-detector separations and multiwavelength light sources to derive absolute placental oxygen saturation (PltO2) and relative cytochrome-c-oxidase (oxCCO) changes. FSM was placed on the abdominal wall following an ultrasound scan locating the placental position. Monte Carlo simulations were performed to estimate placental sensitivity, and a minimum placental sensitivity (MPS) threshold (>5%) defined a physiologically refined sub-cohort. Outcomes were classified using the In Utero near-miss criteria for stillbirth. Machine learning (ML) analysis evaluated 11 classifiers using nested stratified 5 x 4 cross-validation (5 outer folds for performance estimation and 4 inner folds for hyperparameter tuning). ResultsSeventy monitoring sessions from 58 participants were completed across gestational ages (25+2-41+1 weeks gestation); 33 recordings from 30 participants met MPS criteria. In the full cohort, mean PltO2 was 49.8% and was not related to gestational age or poor outcome based on near-miss stillbirth criteria. In the MPS sub-cohort, higher PltO2 was observed in severe fetal growth restriction (FGR) and lower PltO2 in gestational diabetes (both p=0.04). Hemodynamic-metabolic coupling (HbD-oxCCO semblance) was increased in severe FGR (p=0.0002). The best performing ML model (SVM) achieved a balanced accuracy of 78%, a recall (sensitivity) of 72% and a specificity of 84% under 5 x 4 nested cross-validation using the top 50 features. Feature importance analysis identified oxCCO-derived and haemodynamic-metabolic coupling features as dominant predictors, whereas static PltO2 was non-discriminatory. ConclusionWe describe the first wearable NIRS device to provide simultaneous non-invasive placental haemodynamic and metabolic monitoring. While static oxygenation indices lacked predictive value, ML analysis applied to dynamic NIRS features yielded accurate pregnancy outcome prediction, with metabolic signals emerging as key drivers. These findings support further development of wearable placental NIRS integrated with advanced analytics for antenatal surveillance. Condensation pageO_ST_ABSTweetable statementC_ST_ABSA wearable placental near-infrared spectroscopy device enabled real-time monitoring of placental oxygenation and metabolism; machine learning of dynamic signals predicted risk of adverse pregnancy outcomes with 78% balanced accuracy. At a GlanceA. Why was the study conducted? O_LICurrent antenatal surveillance for assessment of fetal wellbeing is suboptimal. C_LIO_LIWe evaluated a wearable near-infrared spectroscopy device for real-time placental monitoring and outcome prediction C_LI B. What are the key findings? O_LIMachine learning applied to dynamic haemodynamic and metabolic optical signals of placental function identified pregnancies at risk with 78% balance accuracy C_LIO_LIPlacental oxygenation was higher in severe fetal growth restriction (FGR) and lower in participants with gestational diabetes (GDM) C_LI C. What does this study add to what is already known O_LIThis is the first wearable near-infrared spectroscopy system to simultaneously monitor real-time changes in placental oxygenation and metabolism in vivo. This is also the first application of machine learning analysis to placental NIRS signals. C_LIO_LIDynamic features of placental metabolism and oxygenation levels may provide clinically meaningful placental biomarkers. C_LI

Patterns and Predictors of Contraceptive Use Among Post-Caesarean Women in Sierra Leone: Insights from a Five-Year Longitudinal Study Caesarean deliveries and short birth intervals predispose to adverse maternal outcomes. Family planning lowers this risk by reducing unplanned pregnancies. This study assessed the uptake and influencing factors of contraceptive use among women at one- and five-years post-caesarean delivery in Sierra Leone. We performed a secondary analysis of data from a multicentre, prospective observational study involving 1,274 women who underwent caesarean delivery in nine hospitals across Sierra Leone between October 2016 and May 2017. The primary outcome was the use of a modern contraceptive method within five years post-delivery. Multivariable logistic regression analyses were used to identify factors associated with contraceptive uptake. Overall contraceptive use at five years was 48.5%. The commonest method used at year one was the intrauterine contraceptive device, but this declined significantly from 40.3% to 0.8% by year five (p[&le;]0.001). Attending more than two antenatal care visits [aOR 1.96; 95% CI (1.19, 3.23)] and offering a contraceptive method before discharge [aOR 2.44; 95% CI (1.05, 6.40)] were associated with a higher likelihood of modern contraceptive uptake, while delivery at a tertiary/regional facility was associated with a lower likelihood [aOR 0.53; 95% CI (0.34, 0.83)]. Increased contact with the health system was associated with a higher uptake of modern contraceptive methods among post-caesarean women. Strengthening provider-client interaction and integrating contraceptive counselling into routine antenatal and postnatal care could improve contraceptive use and address the unmet need for family planning.

BackgroundPreterm birth is one of the most significant etiologies for neonatal morbidity and mortality. Preterm delivery is classified as iatrogenic preterm delivery and spontaneous preterm delivery. The role of placental pathology is studied. Materials and methodsWe have previously collected placental pathology data with maternal pregnancy and neonatal birth data, and we investigated the role of placental pathology in preterm delivery. Preterm delivery was categorized as late preterm (34-36 weeks), moderate preterm (32 to 33 weeks), and extreme preterm (less than 32 weeks). Neonatal, maternal, placental gross and histologic features, and laboratory parameters were compared across groups using chi-square tests for categorical variables and Kruskal-Wallis tests for continuous variables using various programs in R-package. ResultsTotally 3723 singleton placentas including 3307 term (88.8%) and 416 preterm placentas (11.2%) were examined with maternal pregnancy data and neonatal birth data. There were 614 placentas from patients with preeclampsia/pregnancy induced hypertension (PRE/PIH) (16.5%). Preterm delivery showed significantly lower fetal birth weight, placental weight, and fetal-placental ratio (all p<0.01). Maternal Black race was more prevalent in preterm groups (up to 50.8% in extreme preterm vs. 33.2% in term, p<0.01). Preterm delivery was statistically associated with PRE/PIH and maternal vascular malperfusion (MVM), maternal and fetal inflammatory response (MIR and FIR), and increased pre-delivery white blood count (WBC). Extreme preterm deliveries were markedly associated with intrauterine fetal death (27.5%, p<0.01) and MIR/FIR (56.7%, p<0.01). After excluding PRE/PIH patients, preterm delivery was statistically associated with MIR/FIR and increased WBC. ConclusionsDistinct clinicopathologic profiles exist across preterm subcategories, with MVM predominating in late/moderate preterm and severe pathologic features (including fetal demise and acute inflammation) in extreme preterm. These findings highlight heterogeneous etiologies of preterm delivery.

ObjectiveTo evaluate modifiable antepartum and intrapartum factors associated with nulliparous, term, singleton, vertex (NTSV) cesarean delivery and to model risk stratified induction timing strategies that minimize cesarean risk across maternal risk profiles. Study DesignThis retrospective cohort study included all NTSV deliveries at a tertiary care center from January 2015 through August 2025 (overall cohort n=10,525; limited risk cohort n=5,663). Machine learning identified key predictors of cesarean delivery, with maternal age and pre pregnancy body mass index (BMI) used to define low, moderate, and high risk strata. Logistic regression estimated the association between induction and cesarean delivery, and a Monte Carlo simulation compared elective induction at 39, 40, or 41 weeks versus expectant management to 42 weeks within each stratum. ResultsCesarean delivery occurred in 20.1% of the overall cohort and 19.0% of the limited risk cohort, with a U shaped relationship between gestational age and cesarean risk and lowest rates at 38-39 weeks. Induction was associated with higher cesarean rates than spontaneous labor in both cohorts (overall: 24.1% vs. 17.1%; limited risk: 22.9% vs. 15.7%) after adjustment for age, BMI, and gestational age. No single induction policy minimized cesarean risk across all strata. For high risk patients (age >=35 years and BMI >=35), induction at 39 weeks yielded the lowest modeled cesarean rate, whereas later delivery (40 to 41 weeks or expectant management to 41 weeks) was favored for low and moderate risk patients. A universal 39 week induction policy for low and moderate risk strata modestly increased modeled cesarean rates, adding an estimated 46 cesarean deliveries. ConclusionGestational age at delivery and induction strategy are key modifiable determinants of NTSV cesarean delivery, but optimal timing varies by maternal age and BMI risk profile, supporting risk stratified rather than universal 39 week induction policies.

Background: Pregnancy loss, including miscarriage and stillbirth, is a major public health issue with major physical and psychological consequences for pregnant women. Prevalence estimates in low resource settings remain scarce due to the lack of adequate data. This study assessed the prevalence, timing, and maternal characteristics associated with stillbirth and miscarriage using novel longitudinal data collected in five low and middle-income countries (LMICs). Methods and Findings: We analyzed longitudinal data from 5755 pregnant women in Ethiopia, India, Kenya, South Africa, and Cote d'Ivoire. Women were enrolled during pregnancy and followed through delivery. Gestation-specific and cumulative risks of miscarriage and stillbirth were estimated using competing-risks survival analysis, adjusting for timing of enrollment. We examined associations with maternal age, education, wealth, and country using Fine and Gray sub-distribution hazard models. Among pregnancies surviving to 8 weeks, the cumulative risk of pregnancy loss by 28 weeks was 84 per 1,000 pregnancies (95% CI: 69 to 100) and from 28 to 44 weeks the risk was 19 per 1,000 (15 to 24), resulting in a total pregnancy loss risk after 8 weeks of gestation of 103 per 1,000 (88 to 119). Risks were highest in Cote d'Ivoire and lowest in South Africa. Losses peaked between 8 and 6 weeks of gestation, with a secondary rise after 36 weeks. Women aged above 35 years had higher loss risk (HR 1.78, 95% CI: 1.27 to 2.48), whereas wealth and education showed no consistent association. Conclusions: Pregnancy loss remains common across LMICs, with significant risk in both early and late gestation. Conventional estimates that do not account for delayed enrollment underestimate miscarriage rates. Enhanced surveillance and targeted interventions throughout pregnancy, especially during early gestation, are essential to reduce preventable fetal losses and meet associated global goals.

ObjectiveTo evaluate the association between excessive gestational weight gain (GWG) and obstetric and perinatal outcomes among women with pre-pregnancy excess weight attending a public hospital in Lima, Peru. MethodsWe conducted a retrospective cohort study using routinely collected institutional records from Hospital Maria Auxiliadora. Women with singleton pregnancies and pre-pregnancy body mass index (BMI) [&ge;]25 kg/m{superscript 2} who delivered between January 2024 and August 2025 were included. Excessive versus non-excessive GWG was defined according to national guidelines. The primary outcome was a composite obstetric-perinatal outcome. Crude and adjusted relative risks (RRs) were estimated using Poisson regression with robust variance. Effect modification by pre-pregnancy BMI and maternal short stature was evaluated. ResultsOf 6082 records, 3118 met the eligibility criteria; 31.0% had excessive GWG. In adjusted analyses, excessive GWG was associated with a small increase in the risk of the composite outcome (aRR = 1.05; 95% CI: 1.01-1.09), but not with overall obstetric outcomes (aRR = 1.04; 95% CI: 0.99-1.09) or overall perinatal outcomes (aRR = 0.99; 95% CI: 0.85-1.15). The association varied according to pre-pregnancy BMI, with higher relative risks observed among women with obesity (classes I-III). ConclusionsAmong women with pre-pregnancy excess weight, excessive gestational weight gain was associated with a small increase in the risk of composite obstetric-perinatal outcomes but not with obstetric or perinatal outcomes analysed separately. The magnitude of the association differed across BMI categories, with stronger associations in higher obesity classes. These findings emphasise the importance of pre-pregnancy nutritional status when interpreting the potential impact of gestational weight gain on pregnancy outcomes.

Objective: To externally validate a risk stratified delivery timing model for nulliparous, term, singleton, vertex (NTSV) cesarean reduction using national data. Design: Population based cohort study of NTSV births in US National Vital Statistics System (NVSS) natality files, 2020 to2024, using logistic regression for cesarean predictors and risk stratified Monte Carlo simulation (10,000 iterations per strategy and risk group) to evaluate delivery timing policies. Setting: All live births in the US recorded in the NVSS natality files. Participants: NTSV patients with term (37+ weeks) pregnancies and complete gestational age and delivery mode data (N=5 776 412). A sensitivity cohort excluded pre 39 week deliveries and pregnancies with preexisting diabetes or hypertension. Exposures: Delivery timing strategies defined by gestational age and labor onset (elective induction at 39, 40, or 41 weeks, or expectant management to 42 weeks), evaluated within maternal age and body mass index (BMI) risk strata (low: age <35 and BMI <30; moderate: age > 35 or BMI > 30; high: age > 35 and BMI > 35). Main Outcomes and Measures: Primary outcome was cesarean delivery, measured as the proportion of deliveries completed by cesarean across gestational ages, labor onset types, and age BMI strata. Secondary outcomes included gestational age specific cesarean rates, area under the receiver operating characteristic curve (AUC) for cesarean prediction, and simulated mean cesarean rates with 95% simulation intervals under four delivery timing strategies within each risk group. Results: The overall NTSV cesarean rate was 26.4%. Cesarean Rates were U shaped across gestational ages, with the lowest rate at 38 weeks (24.9%) and higher rates at 37 weeks (29.8%) and 41 to 42 weeks (28.1 to 28.5%). Risk group distribution was 64.9% low, 33.7% moderate, and 1.4% high. Model AUC was 0.65. Induction had higher cesarean rates than spontaneous labor (29.3% vs 24.2%; odds ratio 1.30, 95% confidence interval 1.29 to 1.30). Monte Carlo simulation favored induction at 39 weeks for high risk patients (59.3%) and expectant management to 41 to 42 weeks for low risk patients (19.1%). Conclusions and Relevance: A risk stratified NTSV labor management model showed external validity in 5.8 million US births and consistently identified risk-specific timing strategies that lowered cesarean rates, supporting individualized delivery timing policies.

ObjectiveTo retrospectively validate an electronic health record (EHR) implementation of the patient-initiated PreMA screener and compare its association with severe maternal morbidity (SMM) outcomes against established obstetric comorbidity indices. MethodsWe conducted a retrospective observational study using UCSF (single center) and UC-wide (multi-center) de-identified EHR data, identifying live-birth deliveries with documented preconception data. PreMA and established comorbidity index (Bateman and Leonard) scores were computed from preconception diagnoses, standardized to z-scores, and modeled as continuous predictors of SMM and non-transfusion SMM (NT-SMM) using logistic and Poisson regression models, with stratified analyses by race, ethnicity, and neighborhood deprivation. To examine the relationship between individual PreMA questionnaire domains and outcomes, we used adjusted Poisson regression to estimate the association of each domain with SMM and NT-SMM. ResultsAcross both cohorts, higher standardized PreMA, Bateman, and Leonard scores were consistently significantly associated with increased risk of SMM and NT-SMM, with relative risk estimates generally in the [~]1.2-1.4 range per standard deviation (adj. p < 0.001), and similar magnitude across indices and cohorts. Significant associations persisted across racial, ethnic, and socioeconomic, and item-level analyses suggested heterogeneity across PreMA domains, with cardiovascular domains showing the strongest adjusted associations. ConclusionAn EHR-derived PreMA score demonstrated robust, generalizable associations with severe maternal morbidity outcomes comparable to established clinician-facing indices, supporting PreMAs validity as a scalable, patient-centered preconception risk assessment tool.

ObjectivePreterm birth (PTB) is a leading cause of neonatal morbidity and mortality worldwide, with India alone contributing nearly 27% of the global PTB burden. Although alterations in the vaginal microbiome have been implicated in PTB, its association in the Indian context is underexplored. This study aimed to investigate the association of vaginal microbiome and PTB in Indian women at the time of delivery. Study designThe vaginal swabs were collected at the time of delivery from 72 women (31 term, 41 preterm) admitted to a tertiary care hospital in Western India. Microbial DNA was extracted, and the V3-V4 region of the 16S rRNA gene was sequenced. Community composition, alpha and beta diversity, and differential taxonomic abundance were assessed using bioinformatics pipelines. ResultsAt the time of delivery, there were no significant differences in alpha or beta diversity between term and preterm groups. Principal coordinate and unsupervised clustering analyses showed no group-wise segregation. The relative abundance of individual Lactobacillus species, including L. iners and L. helveticus, did not differ significantly between the two groups. However, a modest difference in the relative abundance of Streptococcus was observed between the two groups after adjustment. ConclusionThis study found no major microbial shifts in the vaginal microbiome associated with preterm birth in this cross sectional cohort of Indian women, suggesting that vaginal dysbiosis at the time of delivery may not be a principal driver of PTB in this population. These findings underscore the need for larger, longitudinal, and ethnically diverse studies using standardized methodologies better to understand the microbiomes role in PTB risk.

BackgroundUndernutrition during pregnancy is a major public health issue and may lead to negative pregnancy outcomes. The body mass index (BMI), considered widely used as the reference method for assessing nutritional status due to its established population-based cut-off points; however, it can be misleading in pregnancy. This study aimed to validate the mid-upper arm circumference (MUAC) as a screening tool for identifying undernourished pregnant women (PW) in an urban slum, compared to BMI. MethodsData for this analysis were extracted from studies conducted in Bauniabadh, a slum located in Dhaka, Bangladesh. The final sample size was 375 PW aged 15-39 years with a gestational age of <14 weeks. The first recorded weight during enrolment was considered a proxy for pre-pregnancy weight. Participants were classified as undernourished or well-nourished accordingly. The BMI Z-scores for adolescents and the BMI categories for adult women were used to define undernutrition. Receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC), sensitivity, specificity, predictive values, and likelihood ratios. BMI-MUAC concordance was analyzed using McNemars test to determine optimal MUAC cut-offs. ResultsAmong the candidate MUAC cut-off values, a threshold of <22.5 cm demonstrated high diagnostic accuracy, with 78.1% sensitivity, 92.9% specificity, an AUC of 85.5%, and a positive likelihood ratio (LR+) of 11.0. The alternative threshold of <23.0 cm showed higher sensitivity (84.4%) and AUC (86.9%) but lower specificity (89.4%) and LR+ (7.9). The difference in AUCs between the two thresholds was not statistically significant (p = 0.400). Using the <22.5 cm cut-off, 19.2% of pregnant women were classified as undernourished compared with 17.1% based on BMI. Concordance between MUAC <22.5 cm and BMI-defined undernutrition was satisfactory (p=0.182). ConclusionsMUAC can be considered a simple and effective screening tool for identifying undernutrition in PW. Given its strong diagnostic accuracy, a threshold of <22.5 cm may be a practical alternative to BMI and considered for integration into nutritional programs for PW in Bangladesh.

Introduction Cesarean delivery accounts for nearly one-third of U.S. births and is associated with substantial maternal morbidity and health care costs. Persistent racial disparities have been documented, yet the structural factors contributing to these differences remain incompletely understood. The extent to which insurance coverage shapes racial disparities in cesarean delivery remains unclear. Objective To evaluate the independent and interactive associations of race/ethnicity and insurance coverage with cesarean delivery in the United States. Methods Population-based retrospective cohort study using singleton live births recorded in the United States Vital Statistics Natality files from 2014 to 2024. Multivariable logistic regression was used to estimate the independent effects of race/ethnicity and insurance status on cesarean delivery, including interaction terms to test effect modification, using national birth certificate data. Models were adjusted for maternal demographics, clinical factors, and temporal covariates. Adjusted odds ratios, predicted probabilities, and absolute risk differences were derived from post-estimation marginal effects. The main outcome measure was cesarean delivery (yes vs no). Results Among 41,543,568 deliveries from 2014 to 2024, 13,312,221 (32.0%) were cesarean deliveries. After adjustment, both race and ethnicity and insurance status were independently associated with cesarean delivery. Compared with non-Hispanic White women, non-Hispanic Black women had higher odds of cesarean delivery (odds ratio [OR], 1.22; 95% CI, 1.22-1.23). Relative to uninsured women, those with private insurance had 59% higher odds of cesarean delivery (OR, 1.59; 95% CI, 1.58-1.60). Significant interaction effects were observed, indicating that insurance coverage modified racial and ethnic differences in cesarean delivery. Non-Hispanic Black women had the highest predicted probabilities across all insurance categories, with the largest absolute disparities observed among uninsured women. Conclusion Racial and ethnic differences in cesarean delivery persist in the United States and are modified by insurance coverage, suggesting that coverage-related differences may contribute to inequities in obstetric care.

Childbirth-related posttraumatic stress disorder (PTSD) is an underrecognized maternal morbidity. We tested whether obstetric complications increase risk for later PTSD symptoms through acute peritraumatic distress and early postpartum trauma symptoms. In a prospective cohort of 667 women, acute distress was assessed at 1.44 days postpartum, PTSD symptoms at approximately 10 days and 2 months postpartum, and depression symptoms at 10 days; obstetric complications were abstracted from medical records. Structural equation modeling showed that obstetric complications were associated with greater acute distress ({beta}=0.292, p<0.001), which predicted higher PTSD symptoms at 10 days postpartum ({beta}=0.561, p<0.001); early symptoms predicted symptoms at 2 months ({beta}=0.665, p<0.001). The direct path from obstetric complications to 2-month PTSD symptoms was not significant. A significant serial indirect effect was observed through acute distress and early PTSD symptoms ({beta}=0.109, p<0.001), whereas depression was not a mediator. These findings support early screening for childbirth-related PTSD risk after complicated delivery.

BackgroundRisk screening for pre-eclampsia relies on accurate gestational age assessment, but routine access to ultrasound-based gestational dating remains challenging in many low- and middle-income countries (LMICs). As part of the formative work for the "Preventing pre-eclampsia: Evaluating AspiRin Low-dose regimens following risk Screening" (PEARLS) trial, we aim to validate and implement an Artificial Intelligence (AI)-based algorithm for estimation of gestational age, using blind sweeps done with a handheld ultrasound device. This study protocol outlines the accuracy cohort for AI-based gestational age estimation in participating facilities in Ghana, Kenya, and South Africa. MethodsThis multi-country prospective cohort study will recruit 969 pregnant women at 13 health facilities across Kenya, Ghana and South Africa. The eligible population are pregnant women presenting for antenatal visit from 11+0 to 13+6 weeks gestation. Eligible women will have a gestational age assessment by a trained sonographer using fetal biometry (reference standard), followed by gestational age estimation conducted by a trained midwife using the AI-based Intelligent Ultrasound ScanNav FetalCheck system (experimental). Both conventional and AI-based gestational age scans will be conducted with the General Electric (GE) VScanTM Air platform. Women will return for a second visit between 14+0 and 27+6 weeks gestation (week of visit is randomly selected) for an assessment with both conventional and AI-based ultrasound. The primary objective is to determine the accuracy and precision of gestational age estimation using an AI ultrasound system in first and second trimesters, as compared to gestational age estimation using crown-rump length (CRL) measurement by conventional ultrasound in first trimester (11+0 to 13+6 weeks). DiscussionThe study will provide critical evidence on the accuracy of a point-of-care, AI-based gestational age estimation ultrasound algorithm in sub-Saharan African settings. This study will inform the design of the PEARLS trial, as well as provide vital evidence for expanding implementation of ultrasound-based gestational age assessment for women in Africa.