Use of Real-World Data and Machine Learning to Screen for Maternal and Paternal Characteristics Associated with Cardiac Malformations.

Effective prevention of cardiac malformations, a leading cause of infant morbidity, is constrained by limited understanding of etiology. The study objective was to screen for associations between maternal and paternal characteristics and cardiac malformations. We selected 720,381 pregnancies linked to live-born infants (n=9,076 cardiac malformations) in 2011-2021 MarketScan US insurance claims data. Odds ratios were estimated with clinical diagnostic and medication codes using logistic regression. Screening of 2,000 associations selected 81 associated codes at the 5% false discovery rate. Grouping of selected codes, using latent semantic analysis and the Apriori-SD algorithm, identified elevated risk with known risk factors, including maternal diabetes and chronic hypertension. Less recognized potential signals included maternal fingolimod or azathioprine use. Signals identified might be explained by confounding, measurement error, and selection bias and warrant further investigation. The screening methods employed identified known risk factors, suggesting potential utility for identifying novel risk factors for other pregnancy outcomes.

Patterns of paternal medication dispensation around the time of conception.

BACKGROUND: Past research on the safety of prenatal exposure to medications has focused on maternal use during gestation, with limited research into the potential effects of paternal use during the spermatogenic period preceding conception. Knowing the most common medications used by fathers around the time of conception can inform research priorities in this field. OBJECTIVES: To identify the most common medications dispensed to fathers in the preconception period. METHODS: Within the MarketScan research database of commercially insured individuals in the United States from 2011 to 2020, we identified pregnancies, estimated the date of conception, linked each pregnancy to the father using family enrolment information and required minimum enrolment period and prescription benefits. Then, we described the use of prescription medications by the father during the 90 days before conception based on pharmacy dispensation claims. RESULTS: Of 4,437,550 pregnancies, 51.6% were linked with a father. Among the 1,413,762 pregnancies connected with a father that also met the inclusion criteria, the most common classes of medications dispensed were psychotropics (8.66%), antibiotics (7.21%), and analgesics (6.82%). The most frequently dispensed medications were amoxicillin (3.75%), azithromycin (3.15%), fluticasone (2.70%) and acetaminophen/hydrocodone (2.70%). Some fathers filled prescriptions for medications associated with foetal embryopathy when used by the mother, including mycophenolate (0.04%), methotrexate (0.03%) and isotretinoin (0.02%). CONCLUSIONS: More than a third of fathers filled at least one prescription medication in the preconception period, and several of them are known to be embryotoxic, emphasizing the necessity for further investigation into the potential teratogenicity of paternal exposure.

Perspectives on drug development for the treatment of chronic myeloid leukemia in pregnant patients and patients who are breastfeeding.

Tyrosine kinase inhibitors (TKI) have improved the outcome and life expectancy of patients with chronic myeloid leukemia (CML). Patients are diagnosed with CML at younger ages, and patients treated for CML may become pregnant or choose to breastfeed. The information available to date on the safety of TKIs during pregnancy and lactation and the optimal management of these patients is largely anecdotal, based on personal or small-group experience, and heterogeneous. A panel of interested parties was convened by US Food and Drug Administration (FDA) to analyze the current data and discuss possible solutions. Possible solutions include prospective data collection, in clinical trials and in routine clinical practice, a more uniform and specific data collection, and greater coordination among involved entities. Since patients with cancer are living longer, frequently receiving therapies for extended periods of time (or for life), data on appropriate management of patients through different reproductive phases of life are needed. It is thus time to change our approach for how to study treatment of cancer (including CML) during pregnancy or breastfeeding to develop evidence-based guidelines for safe and effective patient care.

First-trimester exposure to newer antiretroviral agents and congenital anomalies in a U.S. cohort.

OBJECTIVE: To characterize associations of exposure to newer antiretroviral medications in the first trimester with congenital anomalies among infants born to persons with HIV in the United States. DESIGN: Longitudinal cohort of infants born 2012-2022 to pregnant persons with HIV enrolled in the Surveillance Monitoring for ART Toxicities (SMARTT) study. METHODS: First-trimester exposures to newer ARVs were abstracted from maternal medical records. Trained site staff conducted physical exams and abstracted congenital anomalies from infant medical records. Investigators classified anomalies using the Metropolitan Atlanta Congenital Defects Program classification system. The prevalence of major congenital anomalies identified by age one year was estimated for infants exposed and unexposed to each ARV. Generalized estimating equation models were used to estimate the odds ratio (OR) of major congenital anomalies for each ARV exposure, adjusting for potential confounders. RESULTS: Of 2034 infants, major congenital anomalies were identified in 135 (6.6%; 95% CI: 5.6%-7.8%). Cardiovascular (n = 43) and musculoskeletal (n = 37) anomalies were the most common. Adjusted ORs (95% CI) of congenital anomalies were 1.03 (0.62-1.72) for darunavir, 0.91 (0.46-1.81) for raltegravir, 1.04 (0.58-1.85) for rilpivirine, 1.31 (0.71-2.41) for elvitegravir, 0.76 (0.37-1.57) for dolutegravir, and 0.34 (0.05-2.51) for bictegravir, compared to those unexposed to each specific ARV. Findings were similar after adjustment for nucleoside/nucleotide backbones. CONCLUSIONS: The odds of congenital anomalies among infants with first-trimester exposure to newer ARVs did not differ substantially from those unexposed to these specific ARVs, which is reassuring. Continued evaluation of these ARVs with larger studies will be needed to confirm these findings.

Metformin Use in the First Trimester of Pregnancy and Risk for Nonlive Birth and Congenital Malformations: Emulating a Target Trial Using Real-World Data.

BACKGROUND: Metformin is a first-line pharmacotherapy for type 2 diabetes, but there is limited evidence about its safety in early pregnancy. OBJECTIVE: To evaluate the teratogenicity of metformin use in the first trimester of pregnancy. DESIGN: In an observational cohort of pregnant women with pregestational type 2 diabetes receiving metformin monotherapy before the last menstrual period (LMP), a target trial with 2 treatment strategies was emulated: insulin monotherapy (discontinue metformin treatment and initiate insulin within 90 days of LMP) or insulin plus metformin (continue metformin and initiate insulin within 90 days of LMP). SETTING: U.S. Medicaid health care administration database (2000 to 2018). PARTICIPANTS: 12 489 pregnant women who met the eligibility criteria. MEASUREMENTS: The risk and risk ratio of nonlive births, live births with congenital malformations, and congenital malformations among live births were estimated using standardization to adjust for covariates. RESULTS: A total of 850 women were in the insulin monotherapy group and 1557 in the insulin plus metformin group. The estimated risk for nonlive birth was 32.7% under insulin monotherapy (reference) and 34.3% under insulin plus metformin (risk ratio, 1.02 [95% CI, 1.01 to 1.04]). The estimated risk for live birth with congenital malformations was 8.0% (CI, 5.7% to 10.2%) under insulin monotherapy and 5.7% (CI, 4.5% to 7.3%) under insulin plus metformin (risk ratio, 0.72 [CI, 0.51 to 1.09]). LIMITATION: Possible residual confounding by glycemic control and body mass index. CONCLUSION: Compared with switching to insulin monotherapy, continuing metformin and adding insulin in early pregnancy resulted in little to no increased risk for nonlive birth among women receiving metformin before pregnancy. Under conventional statistical criteria, anything between a 49% decrease and a 9% increase in risk for congenital malformations was highly compatible with our data. PRIMARY FUNDING SOURCE: National Institutes of Health.

Paternal Use of Metformin During the Sperm Development Period Preceding Conception and Risk for Major Congenital Malformations in Newborns.

BACKGROUND: Metformin is the most used oral antidiabetic medication. Despite its established safety profile, it has known antiandrogenic and epigenetic modifying effects. This raised concerns about possible adverse developmental effects caused by genomic alterations related to paternal use of metformin during the spermatogenesis period preceding conception. OBJECTIVE: To assess the potential adverse intergenerational effect of metformin by examining the association between paternal metformin use during spermatogenesis and major congenital malformations (MCMs) in newborns. DESIGN: Nationally representative cohort study. SETTING: A large Israeli health fund. PARTICIPANTS: 383 851 live births linked to fathers and mothers that occurred in 1999 to 2020. MEASUREMENTS: MCMs and parental cardiometabolic conditions were ascertained using clinical diagnoses, medication dispensing information, and laboratory test results. The effect of metformin use on MCMs was estimated using general estimating equations, accounting for concurrent use of other antidiabetic medications and parental cardiometabolic morbidity. RESULTS: Compared with unexposed fathers, the prevalence of cardiometabolic morbidity was substantially higher among fathers who used metformin during spermatogenesis, and their spouses. Whereas the crude odds ratio (OR) for paternal metformin exposure in all formulations and MCMs was 1.28 (95% CI, 1.01 to 1.64), the adjusted OR was 1.00 (CI, 0.76 to 1.31). Within specific treatment regimens, the adjusted OR was 0.86 (CI, 0.60 to 1.23) for metformin in monotherapy and 1.36 (CI, 1.00 to 1.85) for metformin in polytherapy, a treatment that was more common in patients with more poorly controlled diabetes. LIMITATION: Laboratory test results for hemoglobin A1c to assess underlying diabetes severity were available only for a subset of the cohort. CONCLUSION: Paternal use of metformin in monotherapy does not increase the risk for MCMs. Association for metformin in polytherapy could potentially be explained by worse underlying parental cardiometabolic risk profile. PRIMARY FUNDING SOURCE: None.

Association between density of food retailers and fitness centers and gestational diabetes mellitus in Eastern Massachusetts, USA: population-based study.

Background: Few studies have investigated the relationship between the food and physical activity environment and odds of gestational diabetes mellitus (GDM). This study quantifies the association between densities of several types of food establishments and fitness centers with the odds of having GDM. Methods: The density of supermarkets, fast-food restaurants, full-service restaurants, convenience stores and fitness centers at 500, 1000 and 1500 m (m) buffers was counted at residential addresses of 68,779 pregnant individuals from Eastern Massachusetts during 2000-2016. The 'healthy food index' assessed the relative availability of healthy (supermarkets) vs unhealthy (fast-food restaurants, convenience stores) food retailers. Multivariable logistic regression quantified the cross-sectional association between exposure variables and the odds of having GDM, adjusting for individual and area-level characteristics. Effect modification by area-level socioeconomic status (SES) was assessed. Findings: In fully adjusted models, pregnant individuals living in the highest density tertile of fast-food restaurants had higher GDM odds compared to those living in the lowest density tertile (500 m: odds ratio (OR):1.17 95% CI: [1.04, 1.31]; 1000 m: 1.33 95% CI: [1.15, 1.53]); 1500 m: 1.18 95% CI: [1.01, 1.38]). Greater residential density of supermarkets was associated with lower odds of GDM (1000 m: 0.86 95% CI: [0.74, 0.99]; 1500 m: 0.86 95% CI: [0.72, 1.01]). Similarly, living in the highest fitness center density tertile was associated with decreased GDM odds (500 m:0.87 95% CI: [0.76, 0.99]; 1500 m: 0.89 95% CI: [0.79, 1.01]). There was no evidence of effect modification by SES and no association found between the healthy food index and GDM odds. Interpretation: In Eastern Massachusetts, living near a greater density of fast-food establishments was associated with higher GDM odds. Greater residential access to supermarkets and fitness centers was associated with lower the odds of having GDM. Funding: NIH.

TNF-α inhibitor use during pregnancy and the risk of preeclampsia: population-based cohort study.

BACKGROUND: Although the clinical importance of preeclampsia is widely recognized, few treatment options are available for prevention. TNF-α inhibitors have been hypothesized to potentially prevent the disease. We aimed to examine whether exposure to TNF-α inhibitors during pregnancy reduces the risk of preeclampsia. METHODS: We conducted a population-based pregnancy cohort study using nationwide samples of publicly (Medicaid data, 2000-2018) and commercially (MarketScan Research Database, 2003-2020) insured pregnant women linked to their liveborn infants. Exposure was ascertained based on a filled prescription or administration code for TNF-α inhibitors during the first and second trimester of pregnancy. The outcomes included early-onset preeclampsia, late-onset preeclampsia, and small-for-gestational age. For baseline confounding adjustment, we leveraged propensity score overlap weights to estimate risk ratios (RR). RESULTS: Among 4 315 658 pregnancies in the Medicaid and the MarketScan cohort, 2736 (0.063%) were exposed to TNF-α inhibitors during the first trimester and 1712 (0.040%) during the second trimester. After adjustment, the risk of early-onset preeclampsia was not decreased among mothers exposed during the first trimester compared with unexposed women with treatment indications [RRpooled: 1.25, 95% confidence interval (CI) 0.93-1.67]. Similarly, the risk of late-onset preeclampsia was not decreased among mothers exposed during the second trimester compared with unexposed women (RRpooled: 0.99, 95% CI 0.81-1.22). CONCLUSION: Contrary to the hypothesis, exposure to TNF-α inhibitors during pregnancy did not appear to be associated with a reduced risk of early-onset or late-onset preeclampsia. These findings do not support consideration of the use of TNF-α inhibitors for the prevention of preeclampsia.

The association of short-term increases in ambient PM2.5 and temperature exposures with stillbirth: racial/ethnic disparities among Medicaid recipients.

Racial/ethnic disparities in the association between short-term (e.g. days, weeks) ambient fine particulate matter (PM2.5) and temperature exposures and stillbirth in the US have been understudied. A time-stratified, case-crossover design using a distributed lag non-linear model (0 to 6-day lag) estimated stillbirth odds due to short-term increases in average daily PM2.5 and temperature exposures among 118,632 Medicaid recipients from 2000-2014. Disparities by maternal race/ethnicity (Black, White, Hispanic, Asian, American Indian) and zip-code level socioeconomic status (SES) were assessed. In the temperature-adjusted model, a 10 µg/m3 increase in PM2.5 concentration was marginally associated with increased stillbirth odds at lag 1 (0.68% 95%CI:[-0.04,1.40]) and lag 2 (0.52% 95%CI:[-0.03,1.06]), but not lag 0-6 (2.80% 95%CI:[-0.81,6.45]). An association between daily PM2.5 concentrations and stillbirth odds was found among Black individuals at the cumulative lag (0-6 days: 9.26% 95%CI:[3.12,15.77]), but not among other races/ethnicities. A stronger association between PM2.5 concentrations and stillbirth odds existed among Black individuals living in zip codes with the lowest median household income (lag0-6:14.13% 95%CI:[4.64,25.79]). Short-term temperature increases were not associated with stillbirth risk among any race/ethnicity. Black Medicaid enrollees, and especially those living in lower SES areas, may be more vulnerable to stillbirth due to short-term increases in PM2.5 exposure.

Prognostic significance of sentinel lymph node biopsy in elderly with cutaneous melanoma: systematic review and meta-analysis.

Sentinel lymph node biopsy is the most powerful prognostic indicator to date for cutaneous melanoma. Even though elderly patients have a lower incidence of sentinel node involvement, its results are still necessary for access to adjuvant therapies. This is highly relevant considering that the Western population shows an aging trend, and the incidence of melanoma has grown exponentially over the years, making elderly patients more likely to die from melanoma than younger ones. We performed a systematic review to investigate the prognostic significance of sentinel lymph node biopsy in elderly patients with melanoma. The systematic review was conducted following the PRISMA guidelines and registered in PROSPERO. The authors searched the Cochrane Database, EMBASE, PubMed, and WOS. Eligible studies for the systematic review were clinical trials, observational population studies, clinical or hospital-based cohort studies, and case-control studies. The meta-analysis was conducted using the R software program applying the meta package. Six reports were identified to meet the inclusion criteria. All studies were retrospective, non-randomized cohorts. The results obtained in this systematic review show a statistically significant influence of sentinel lymph node biopsy on disease-specific survival (HR = 2.87; 95% CI: 1.73-4.74) but also suggest that a positive result negatively impacts disease-free survival (HR = 3.41; 95% CI: 0.96-12.11). This meta-analysis shows that a positive sentinel lymph node biopsy does not imply differences in overall survival but significantly influences disease-specific survival and suggests an unfavorable impact on disease-free survival.

Internal validation of gestational age estimation algorithms in healthcare databases using pregnancies conceived with fertility procedures.

Fertility procedures recorded in healthcare databases can be used to estimate the start of pregnancy, which can serve as a reference standard to validate gestational age estimates based on International Classification of Diseases (ICD) codes. In a cohort of 17,398 pregnancies conceived by fertility procedures in MarketScan (2011-2020), we estimated gestational age at the end of pregnancy using algorithms based on (1) days since fertility procedure (the reference); (2) ICD-9/ICD-10 (before/after October 2015) codes indicating gestational length recorded at the end of pregnancy (method A); and (3) ICD-10 enhanced with Z3A codes denoting specific gestation weeks recorded at prenatal visits (method B). We calculated the proportion of pregnancies with an estimated gestational age within 14 days of the reference. Method A accuracy was similar for ICD-9 and ICD-10 codes. After 2015, method B was more accurate than method A: For term births, within-14-day-agreements were 90.8% for method A and 98.7% for method B. Corresponding estimates were 70.1% and 95.6% for preterm births; 35.3% and 92.6% for stillbirths; 54.3% and 64.2% for spontaneous abortions; and 16.7% and 84.6% for elective terminations. ICD-10-based algorithms that incorporate Z3A codes improve the accuracy of gestational age estimation in healthcare databases, especially for preterm and non-live births.

Risk of Autism after Prenatal Topiramate, Valproate, or Lamotrigine Exposure.

BACKGROUND: Maternal use of valproate during pregnancy has been associated with an increased risk of neurodevelopmental disorders in children. Although most studies of other antiseizure medications have not shown increased risks of these disorders, there are limited and conflicting data regarding the risk of autism spectrum disorder associated with maternal topiramate use. METHODS: We identified a population-based cohort of pregnant women and their children within two health care utilization databases in the United States, with data from 2000 through 2020. Exposure to specific antiseizure medications was defined on the basis of prescription fills from gestational week 19 until delivery. Children who had been exposed to topiramate during the second half of pregnancy were compared with those unexposed to any antiseizure medication during pregnancy with respect to the risk of autism spectrum disorder. Valproate was used as a positive control, and lamotrigine was used as a negative control. RESULTS: The estimated cumulative incidence of autism spectrum disorder at 8 years of age was 1.9% for the full population of children who had not been exposed to antiseizure medication (4,199,796 children). With restriction to children born to mothers with epilepsy, the incidence was 4.2% with no exposure to antiseizure medication (8815 children), 6.2% with exposure to topiramate (1030 children), 10.5% with exposure to valproate (800 children), and 4.1% with exposure to lamotrigine (4205 children). Propensity score-adjusted hazard ratios in a comparison with no exposure to antiseizure medication were 0.96 (95% confidence interval [CI], 0.56 to 1.65) for exposure to topiramate, 2.67 (95% CI, 1.69 to 4.20) for exposure to valproate, and 1.00 (95% CI, 0.69 to 1.46) for exposure to lamotrigine. CONCLUSIONS: The incidence of autism spectrum disorder was higher among children prenatally exposed to the studied antiseizure medications than in the general population. However, after adjustment for indication and other confounders, the association was substantially attenuated for topiramate and lamotrigine, whereas an increased risk remained for valproate. (Funded by the National Institute of Mental Health.).

Metabolic syndrome is not associated with erosive hand osteoarthritis: a cross-sectional study using data from the PROCOAC cohort.

To delineate the phenotype of erosive hand osteoarthritis (EHOA) in a Spanish population and assess its correlation with metabolic syndrome. We conducted a cross-sectional study using baseline data from the Prospective Cohort of Osteoarthritis from A Coruña (PROCOAC). Demographic and clinical variables, obtained through questionnaires, clinical examinations, and patient analytics, were compared among individuals with hand OA, with and without EHOA. We performed appropriate univariate and multivariate stepwise regression analyses using SPSS v28. Among 1039 subjects diagnosed with hand OA, 303 exhibited EHOA. Multivariate logistic regression analysis revealed associations with inflamed joints, nodular hand OA, and total AUSCAN. Furthermore, the association with a lower prevalence of knee OA remained significant. The influence of metabolic syndrome (MetS) on EHOA patients was analyzed by including MetS as a covariate in the model. It was observed that MetS does not significantly impact the presence of EHOA, maintaining the effect size of other factors. In conclusion, in the PROCOAC cohort, EHOA is associated with nodular hand OA, inflammatory hand OA, and a higher total AUSCAN. However, EHOA is linked to a lower prevalence of knee OA. Importantly, in our cohort, no relationship was found between EHOA and MetS.

Prediction of bronchopulmonary dysplasia in very preterm infants: competitive risk model nomogram.

Objective: To develop predictive clinical models of bronchopulmonary dysplasia (BPD) through competing risk analysis. Methods: Retrospective observational cohort study, including preterm newborns ≤32 weeks gestational age, conducted between January 1, 2013 and September 30, 2022 in a third-level Neonatal Intensive Care Unit in Spain. A prediction study was carried out using competing risk models, where the event of interest was BPD and the competing event was death. A multivariate competing risk model was developed separately for each postnatal day (days 1, 3, 7 and 14). Nomograms to predict BPD risk were developed from the coefficients of the final models and internally validated. Results: A total of 306 patients were included in the study, of which 73 (23.9%) developed BPD and 29 (9.5%) died. On day 1, the model with the greatest predictive capacity was that including birth weight, days since rupture of membranes, and surfactant requirement (area under the receiver operating characteristic (ROC) curve (AUC), 0.896; 95% CI, 0.792-0.999). On day 3, the final predictive model was based on the variables birth weight, surfactant requirement, and Fraction of Inspired Oxygen (FiO2) (AUC, 0.891; 95% CI, 0.792-0.989). Conclusions: Competing risk analysis allowed accurate prediction of BPD, avoiding the potential bias resulting from the exclusion of deceased newborns or the use of combined outcomes. The resulting models are based on clinical variables measured at bedside during the first 3 days of life, can be easily implemented in clinical practice, and can enable earlier identification of patients at high risk of BPD.

Accounting for Twins and Other Multiple Births in Perinatal Studies Conducted Using Healthcare Administration Data.

The analysis of perinatal studies is complicated by twins and other multiple births even when they are not the exposure, outcome, or a confounder of interest. Common approaches to handling multiples in studies of infant outcomes include restriction to singletons, counting outcomes at the pregnancy-level (i.e., by counting if at least one twin experienced a binary outcome), or infant-level analysis including all infants and, typically, accounting for clustering of outcomes by using generalised estimating equations or mixed effects models. Several healthcare administration databases only support restriction to singletons or pregnancy-level approaches. For example, in MarketScan insurance claims data, diagnoses in twins are often assigned to a single infant identifier, thereby preventing ascertainment of infant-level outcomes among multiples. Different approaches correspond to different causal questions, produce different estimands, and often rely on different assumptions. We demonstrate the differences that can arise from these different approaches using Monte Carlo simulations, algebraic formulas, and an applied example. Furthermore, we provide guidance on the handling of multiples in perinatal studies when using healthcare administration data.

Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.

OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART). DESIGN: A nation-wide register-based cohort study with prospectively collected data. SETTING: Swedish national registers and nationwide quality IVF register. PATIENT(S): all nulliparous women who achieved birth within the first 3 ART treatment cycles between 2008 and 2016 in Sweden. INTERVENTION(S): Characteristics before the use of ART, such as demographics and medical history, were considered potential predictors in the development of before treatment prediction models. ART treatment details were further included in after treatment prediction models. MAIN OUTCOME MEASURE(S): Potential diagnoses of preeclampsia, placental complications (previa, accreta, and abruption), and postpartum hemorrhage were identified using the International Classification of Diseases recorded in the Swedish Medical Birth and Patient registers, respectively. Multiple prediction model algorithms were performed and compared for each outcome and treatment cycle, including logistic regression, decision tree model, naïve Bayes classification, support vector machine, random forest, and gradient boosting. The performance of each model was assessed with C statistic, and nested cross-validation was used to aid model selection and hyperparameter tuning. RESULT(S): A total of 14,732 women gave birth after the first (N = 7,302), second (N = 4,688), or third (N = 2,742) ART cycle, representing birth rates of 24.1%, 23.8%, and 22.0%. Overall prediction performance did not vary much across the different methods used. In the first cycle, the before treatment prediction performance was at best 66%, 66%, and 60% for preeclampsia, placental complications, and postpartum hemorrhage, respectively. Inclusion of after treatment characteristics conferred slight improvement (approximately 1%-5%), as did prediction in later cycles (approximately 1%-5%). The top influential and consistent predictors included age, region of residence, infertility diagnosis, and type of embryo transfer (fresh or frozen) in the later (2nd and 3rd) cycles. Body mass index was a top predictor of preeclampsia and was also influential for placental complications but not for postpartum hemorrhage. CONCLUSION(S): The combined use of demographics, medical history, and ART treatment information was not enough to confidently predict serious pregnancy complications in women who conceived with ART. Future studies are needed to assess if additional longitudinal follow-up during pregnancy can improve the prediction to allow clinical protocol development.

First Trimester Use of Buprenorphine or Methadone and the Risk of Congenital Malformations.

Importance: Use of buprenorphine or methadone to treat opioid use disorder is recommended in pregnancy; however, their teratogenic potential is largely unknown. Objective: To compare the risk of congenital malformations following in utero exposure to buprenorphine vs methadone. Design, Setting, and Participants: This population-based cohort study used health care utilization data from publicly insured Medicaid beneficiaries in the US from 2000 to 2018. A total of 13 360 pregnancies with enrollment from 90 days prior to pregnancy start through 1 month after delivery and first trimester use of buprenorphine or methadone were included and linked to infants. Data were analyzed from July to December 2022. Exposure: A pharmacy dispensing of buprenorphine or a code for administration of methadone in the first trimester. Main Outcomes and Measures: Primary outcomes included major malformations overall and malformations previously associated with opioids (any cardiac malformations, ventricular septal defect, secundum atrial septal defect/nonprematurity-related patent foramen ovale, neural tube defects, clubfoot, and oral clefts). Secondary outcomes included other organ system-specific malformations. Risk differences and risk ratios (RRs) were estimated comparing buprenorphine with methadone, adjusting for confounders with propensity score overlap weights. Results: The cohort included 9514 pregnancies with first-trimester buprenorphine exposure (mean [SD] maternal age, 28.4 [4.6] years) and 3846 with methadone exposure (mean [SD] maternal age, 28.8 [4.7] years). The risk of malformations overall was 50.9 (95% CI, 46.5-55.3) per 1000 pregnancies for buprenorphine and 60.6 (95% CI, 53.0-68.1) per 1000 pregnancies for methadone. After confounding adjustment, buprenorphine was associated with a lower risk of malformations compared with methadone (RR, 0.82; 95% CI, 0.69-0.97). Risk was lower with buprenorphine for cardiac malformations (RR, 0.63; 95% CI, 0.47-0.85), including both ventricular septal defect (RR, 0.62; 95% CI, 0.39-0.98) and secundum atrial septal defect/nonprematurity-related patent foramen ovale (RR, 0.54; 95% CI, 0.30-0.97), oral clefts (RR, 0.65; 95% CI, 0.35-1.19), and clubfoot (RR, 0.55; 95% CI, 0.32-0.94). Results for neural tube defects were uncertain given low event counts. In secondary analyses, buprenorphine was associated with a decreased risk of central nervous system, urinary, and limb malformations but a greater risk of gastrointestinal malformations compared with methadone. These findings were consistent in sensitivity and bias analyses. Conclusions and Relevance: In this cohort study, the risk of most malformations previously associated with opioid exposure was lower in buprenorphine-exposed infants compared with methadone-exposed infants, independent of measured confounders. Malformation risk is one factor that informs the individualized patient decision regarding medications for opioid use disorder in pregnancy.

Short-Term Increases in NO2 and O3 Concentrations during Pregnancy and Stillbirth Risk in the U.S.: A Time-Stratified Case-Crossover Study.

Associations between gaseous pollutant exposure and stillbirth have focused on exposures averaged over trimesters or gestation. We investigated the association between short-term increases in nitrogen dioxide (NO2) and ozone (O3) concentrations and stillbirth risk among a national sample of 116 788 Medicaid enrollees from 2000 to 2014. A time-stratified case-crossover design was used to estimate distributed (lag 0-lag 6) and cumulative lag effects, which were adjusted for PM2.5 concentration and temperature. Effect modification by race/ethnicity and proximity to hydraulic fracturing (fracking) wells was assessed. Short-term increases in the NO2 and O3 concentrations were not associated with stillbirth in the overall sample. Among American Indian individuals (n = 1694), a 10 ppb increase in NO2 concentrations was associated with increased stillbirth odds at lag 0 (5.66%, 95%CI: [0.57%, 11.01%], p = 0.03) and lag 1 (4.08%, 95%CI: [0.22%, 8.09%], p = 0.04) but not lag 0-6 (7.12%, 95%CI: [-9.83%, 27.27%], p = 0.43). Among participants living in zip codes within 15 km of active fracking wells (n = 9486), a 10 ppb increase in NO2 concentration was associated with increased stillbirth odds in single-day lags (2.42%, 95%CI: [0.37%, 4.52%], p = 0.02 for lag 0 and 1.83%, 95%CI: [0.25%, 3.43%], p = 0.03 for lag 1) but not the cumulative lag (lag 0-6) (4.62%, 95%CI: [-2.75%, 12.55%], p = 0.22). Odds ratios were close to the null in zip codes distant from fracking wells. Future studies should investigate the role of air pollutants emitted from fracking and potential racial disparities in the relationship between short-term increases in NO2 concentrations and stillbirth.