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.).

Buprenorphine versus Methadone for Opioid Use Disorder in Pregnancy.

BACKGROUND: Opioid agonist therapy is strongly recommended for pregnant persons with opioid use disorder. Buprenorphine may be associated with more favorable neonatal and maternal outcomes than methadone, but existing data are limited. METHODS: We conducted a cohort study involving pregnant persons who were enrolled in public insurance programs in the United States during the period from 2000 through 2018 in which we examined outcomes among those who received buprenorphine as compared with those who received methadone. Exposure to the two medications was assessed in early pregnancy (through gestational week 19), late pregnancy (gestational week 20 through the day before delivery), and the 30 days before delivery. Risk ratios for neonatal and maternal outcomes were adjusted for confounders with the use of propensity-score overlap weights. RESULTS: The data source for the study consisted of 2,548,372 pregnancies that ended in live births. In early pregnancy, 10,704 pregnant persons were exposed to buprenorphine and 4387 to methadone. In late pregnancy, 11,272 were exposed to buprenorphine and 5056 to methadone (9976 and 4597, respectively, in the 30 days before delivery). Neonatal abstinence syndrome occurred in 52.0% of the infants who were exposed to buprenorphine in the 30 days before delivery as compared with 69.2% of those exposed to methadone (adjusted relative risk, 0.73; 95% confidence interval [CI], 0.71 to 0.75). Preterm birth occurred in 14.4% of infants exposed to buprenorphine in early pregnancy and in 24.9% of those exposed to methadone (adjusted relative risk, 0.58; 95% CI, 0.53 to 0.62); small size for gestational age in 12.1% and 15.3%, respectively (adjusted relative risk, 0.72; 95% CI, 0.66 to 0.80); and low birth weight in 8.3% and 14.9% (adjusted relative risk, 0.56; 95% CI, 0.50 to 0.63). Delivery by cesarean section occurred in 33.6% of pregnant persons exposed to buprenorphine in early pregnancy and 33.1% of those exposed to methadone (adjusted relative risk, 1.02; 95% CI, 0.97 to 1.08), and severe maternal complications developed in 3.3% and 3.5%, respectively (adjusted relative risk, 0.91; 95% CI, 0.74 to 1.13). Results of exposure in late pregnancy were consistent with results of exposure in early pregnancy. CONCLUSIONS: The use of buprenorphine in pregnancy was associated with a lower risk of adverse neonatal outcomes than methadone use; however, the risk of adverse maternal outcomes was similar among persons who received buprenorphine and those who received methadone. (Funded by the National Institute on Drug Abuse.).

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.

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.

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 (eg, days, weeks), ambient fine particulate matter (PM2.5) and temperature exposures and stillbirth in the United States have been understudied. A time-stratified, case-crossover design using a distributed lag nonlinear model (0- to 6-day lag) was used to estimate stillbirth odds due to short-term increases in average daily PM2.5 and temperature exposures among 118 632 Medicaid recipients from 2000 to 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 m-3 increase in PM2.5 concentration was marginally associated with increased stillbirth odds at lag 1 (0.68%; 95% CI, -0.04% to 1.40%) and lag 2 (0.52%; 95% CI, -0.03 to 1.06) but not lag 0-6 (2.80%; 95% CI, -0.81 to 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 or 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 (lag 0-6: 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. This article is part of a Special Collection on Environmental Epidemiology.

Internal validation of gestational age estimation algorithms in health-care databases using pregnancies conceived through fertility procedures.

Fertility procedures recorded in health-care 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 codes. In a cohort of 17 398 US MarketScan pregnancies (2011-2020) in which conception was achieved via fertility procedures, we estimated gestational age at the end of pregnancy using algorithms based on (1) time (days) since the fertility procedure (the reference standard); (2) International Classification of Diseases, Ninth Revision (ICD-9)/International Classification of Diseases, Tenth Revision (ICD-10) (before/after October 2015) codes indicating gestational length recorded at the end of pregnancy (method A); and (3) ICD-10 end-of-pregnancy codes 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 falling within 14 days ($\pm$14 days) of the reference standard. 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 agreement was 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 health-care databases, especially for preterm births and non-live births.

Development and Validation of an Algorithm to Predict Stillbirth Gestational Age in Medicaid Billing Records.

INTRODUCTION: With Medicaid covering half of US pregnancies, Medicaid Analytic eXtract (MAX) provides a valuable data source to enrich understanding about stillbirth etiologies. OBJECTIVE: We developed and validated a claims-based algorithm to predict GA at stillbirth. METHOD: We linked the stillbirths identified in MAX 1999-2013 to Florida Fetal Death Records (FDRs) to obtain clinical estimates of GA (N=825). We tested several algorithms including using a fixed median GA, median GA at the time of specific prenatal screening tests, and expanded versions considering additional predictors of stillbirth within including linear regression and random forest models. We estimated the proportion of pregnancies with differences of ± 1, 2, 3 and 4 weeks between the predicted and FDR GA and the model mean square error (MSE). We validated the selected algorithms in two external samples. RESULTS: The best performing algorithm was a random forest model (MSE of 12.67 weeks2) with 84% of GAs within ± 4 weeks. Assigning a fixed GA of 28 weeks resulted in an MSE of 60.21 weeks2 and proportions of GA within ± 4 weeks of 32%. We observed consistent results in the external samples. DISCUSSION: Our prediction algorithm for stillbirths can facilitate pregnancy research in the Medicaid population.

Hierarchical Clustering Analysis to Inform Classification of Congenital Malformations for Surveillance of Medication Safety in Pregnancy.

There is growing interest in the secondary use of healthcare data to evaluate medication safety in pregnancy. Tree-based scan statistics (TBSS) offer an innovative approach to help identify potential safety signals. TBSS utilize hierarchically organized outcomes, generally based on existing clinical coding systems that group outcomes by organ system. When assessing teratogenicity, such groupings often lack a sound embryologic basis given the etiologic heterogeneity of congenital malformations. The study objective was to enhance the grouping of congenital malformations to be used in scanning approaches through implementation of hierarchical clustering analysis (HCA) and to pilot test an HCA-enhanced TBSS approach for medication safety surveillance in pregnancy in two test cases using >4.2 million mother-child dyads from two US-nationwide databases. HCA identified (1) malformation combinations belonging to the same organ system already grouped in existing classifications, (2) known combinations across different organ systems not previously grouped, (3) unknown combinations not previously grouped, and (4) malformations seemingly standing on their own. Testing the approach with valproate and topiramate identified expected signals, and a signal for an HCA-cluster missed by traditional classification. Augmenting existing classifications with clusters identified through large data exploration may be promising when defining phenotypes for surveillance and causal inference studies.

Development and validation of claims-based algorithms for estimating gestational age of spontaneous abortion and termination.

To study the risk of spontaneous abortion (SAB) or termination using healthcare utilization databases, algorithms to estimate the gestational age (GA) are needed. Using Medicaid data, we developed a hierarchical algorithm to classify pregnancy outcomes. We identified the subset of potential SAB and termination cases, and abstracted the GA from linked electronic medical records (gold standard). We developed three approaches: (1) assign median GA for SAB and termination cases in the US; (2) draw a random GA from the population distributions; (3) estimate GA based on regression models. Algorithm performance was assessed based on the proportion of pregnancies with estimated GA within 1-4 weeks of the gold standard, the mean squared error (MSE) and the R-squared. Approach 1 and Approach 3 had similar performance, though approach 3 using random forest models with variables selected via the Boruta algorithm had better MSE and R-squared. For SAB, 58.0% of pregnancies were correctly classified within 2 weeks of the gold standard (MSE: 8.7, R-squared: 0.09). For termination, the proportions were 66.3% (MSE: 11.7; R-squared: 0.35). SABs and terminations can be studied in healthcare utilization data with careful implementation of validated algorithms though higher level of GA misclassification is expected compared to live births.

Maternal periconception hyperglycemia, preconception diabetes, and risk of major congenital malformations in offspring.

STUDY QUESTION: What are the roles of maternal preconception diabetes and related periconceptional hyperglycemia on the risk of major congenital malformations (MCMs) in offspring? SUMMARY ANSWER: Maternal periconceptional glycated hemoglobin (HbA1c) levels over 5.6% were associated with an increased risk of congenital heart defects (CHD) in the offspring, and maternal preconception diabetes was associated with an increased risk of CHD, including when HbA1c levels were within euglycemic ranges. WHAT IS KNOWN ALREADY: Maternal preconception diabetes has been linked with MCMs in the offspring. However, evidence concerning associations with specific periconception serum measures of hyperglycemia, and susceptibility of different organ systems, is inconsistent. Moreover, limited evidence exists concerning the effectiveness of antidiabetic medications in mitigating diabetes-related teratogenic risks. STUDY DESIGN, SIZE, DURATION: A large Israeli birth cohort of 46 534 children born in 2001-2020. PARTICIPANTS/MATERIALS, SETTING, METHODS: Maternal HbA1c test results were obtained from 90 days before conception to mid-pregnancy. Maternal diabetes, other cardiometabolic conditions, and MCMs in newborns were ascertained based on clinical diagnoses, medication dispensing records, and laboratory test results using previously validated algorithms. Associations were modeled using generalized additive logistic regression models with thin plate penalized splines. MAIN RESULTS AND THE ROLE OF CHANCE: Maternal periconceptional HbA1c value was associated with CHD in newborns, with the risk starting to increase at HbA1c values exceeding 5.6%. The association between HbA1c and CHD was stronger among mothers with type 2 diabetes mellitus (T2DM) compared to the other diabetes groups. Maternal pre-existing T2DM was associated with CHD even after accounting for HbA1C levels and other cardiometabolic comorbidities (odds ratio (OR)=1.89, 95% CI 1.18, 3.03); and the OR was materially unchanged when only mothers with pre-existing T2DM who had high adherence to antidiabetic medications and normal HbA1c levels were considered. LIMITATIONS, REASONS FOR CAUTION: The rarity of some specific malformation groups limited the ability to conduct more granular analyses. The use of HbA1c as a time-aggregated measure of glycemic control may miss transient glycemic dysregulation that could be clinically meaningful for teratogenic risks. WIDER IMPLICATIONS OF THE FINDINGS: The observed association between pre-existing diabetes and the risk of malformations within HbA1c levels suggests underlying causal pathways that are partly independent of maternal glucose control. Therefore, treatments for hyperglycemia might not completely mitigate the teratogenic risk associated with maternal preconception diabetes. STUDY FUNDING/COMPETING INTEREST(S): The work was supported by NIH grants K99ES035433, R01HD097778, and P30ES000002. None of the authors reports competing interests. TRIAL REGISTRATION NUMBER: N/A.

Prescription medication use during pregnancy in the United States from 2011 to 2020: trends and safety evidence.

BACKGROUND: Medication use during pregnancy has increased in the United States despite the lack of safety data for many medications. OBJECTIVE: This study aimed to inform research priorities by examining trends in medication use during pregnancy and identifying gaps in safety information on the most commonly prescribed medications. STUDY DESIGN: We identified population-based cohorts of commercially (MarketScan 2011-2020) and publicly (Medicaid Analytic eXtract/Transformed Medicaid Statistical Information System Analytic Files 2011-2018) insured pregnancies ending in live birth from 2 health care utilization databases. Medication use was based on filled prescriptions between the date of last menstrual period through delivery, as well as the period before the last menstrual period and during specific trimesters. We also included a cross-sectional representative sample of pregnancies ascertained by the National Health and Nutrition Examination Survey (2011-2020), with information on prescription medication use during the preceding month obtained through maternal interviews. Teratogen Information System was used to classify the available evidence on teratogenic risk. RESULTS: Among over 3 million pregnancies, the medications most commonly dispensed at any time during pregnancy were analgesics, antibiotics, and antiemetics. The top medications were ondansetron (16.8%), amoxicillin (13.5%), and azithromycin (12.4%) in MarketScan, nitrofurantoin (22.2%), acetaminophen (21.3%; mostly as part of acetaminophen-hydrocodone products), and ondansetron (19.5%) in Medicaid Analytic eXtract/Transformed Medicaid Statistical Information System Analytic Files, and levothyroxine (5.0%), sertraline (2.9%), and insulin (2.9%) in the National Health and Nutrition Examination Survey group. The most commonly dispensed suspected teratogens during the first trimester were antithyroid medications. The use of antidiabetic and psychotropic medications has continued to increase in the United States during the last decade, opioid dispensation has decreased by half, and antibiotics and antiemetics continue to be common. For one-quarter of medications, there is insufficient evidence available to characterize their safety profile in pregnancy. CONCLUSION: There is a need for more drug research in pregnant patients. Future research should focus on anti-infectives with high utilization and limited level of evidence on safety for use during pregnancy. Although lack of evidence is not evidence of safety concerns, it does not indicate risk either. In many instances, the benefits outweigh the risks when these medications are used clinically, and some of the medications with no proven safety may be necessary to treat patients.

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.

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.

Changes in Induced Medical and Procedural Abortion Rates in a Commercially Insured Population, 2018 to 2022 : An Interrupted Time-Series Analysis.

BACKGROUND: During the COVID-19 pandemic, access to in-person care was limited, and regulations requiring in-person dispensing of mifepristone for medical abortions were relaxed. The effect of the pandemic and accompanying regulatory changes on abortion use is unknown. OBJECTIVE: To estimate changes in the incidence rate of induced medical and procedural abortions. DESIGN: Serial cross-sectional study with interrupted time-series analyses. SETTING: Commercially insured persons in the United States. PARTICIPANTS: Reproductive-aged women. INTERVENTION: Onset of the COVID-19 pandemic in March 2020 and subsequent regulatory changes affecting the in-person dispensing requirement for mifepristone. MEASUREMENTS: Monthly age-adjusted incidence rates of medical and procedural abortions were measured among women aged 15 to 44 years from January 2018 to June 2022. Medical abortions were classified as in-person or telehealth. Linear segmented time-series regression was used to calculate changes in abortion rates after March 2020. RESULTS: In January 2018, the estimated age-adjusted monthly incidence rate of abortions was 151 per million women (95% CI, 142 to 161 per million women), with equal rates of medical and procedural abortions. After March 2020, there was an immediate 14% decrease in the monthly incidence rate of abortions (21 per million women [CI, 7 to 35 per million women]; P = 0.004), driven by a 31% decline in procedural abortions (22 per million women [CI, 16 to 28 per million women]; P < 0.001). Fewer than 4% of medical abortions each month were administered via telehealth. LIMITATION: Only abortions reimbursed by commercial insurance were measured. CONCLUSION: The incidence rate of procedural abortions declined during the COVID-19 pandemic, and this lower rate persisted after other elective procedures rebounded to prepandemic rates. Despite removal of the in-person dispensing requirement for mifepristone, the use of telehealth for insurance-covered medical abortions remained rare. Amid increasing state restrictions, commercial insurers have the opportunity to increase access to abortion care, particularly via telehealth. PRIMARY FUNDING SOURCE: Health Resources and Services Administration.

Comparative Safety of In Utero Exposure to Buprenorphine Combined With Naloxone vs Buprenorphine Alone.

Importance: Buprenorphine combined with naloxone is commonly used to treat opioid use disorders outside of pregnancy. In pregnancy, buprenorphine alone is generally recommended because of limited perinatal safety data on the combination product. Objective: To compare perinatal outcomes following prenatal exposure to buprenorphine with naloxone vs buprenorphine alone. Design, Settings, and Participants: Population-based cohort study using health care utilization data from Medicaid-insured beneficiaries in the US from 2000 to 2018. The cohort was restricted to pregnant individuals linked to their liveborn infants, with maternal Medicaid enrollment from 3 months before pregnancy to 1 month after delivery and infant enrollment for the first 3 months after birth, unless they died sooner. Exposure: Use of buprenorphine with naloxone vs buprenorphine alone during the first trimester based on outpatient dispensings. Main Outcomes and Measures: Outcomes included major congenital malformations, low birth weight, neonatal abstinence syndrome, neonatal intensive care unit admission, preterm birth, respiratory symptoms, small for gestational age, cesarean delivery, and maternal morbidity. Confounder-adjusted risk ratios were calculated using propensity score overlap weights. Results: This study identified 3369 pregnant individuals exposed to buprenorphine with naloxone during the first trimester (mean [SD] age, 28.8 [4.6] years) and 5326 exposed to buprenorphine alone or who switched from the combination to buprenorphine alone by the end of the first trimester (mean [SD] age, 28.3 [4.5] years). When comparing buprenorphine combined with naloxone with buprenorphine alone, a lower risk for neonatal abstinence syndrome (absolute risk, 37.4% vs 55.8%; weighted relative risk, 0.77 [95% CI, 0.70-0.84]) and a modestly lower risk for neonatal intensive care unit admission (absolute risk, 30.6% vs 34.9%; weighted relative risk, 0.91 [95% CI, 0.85-0.98]) and small for gestational age (absolute risk, 10.0% vs 12.4%; weighted relative risk, 0.86 [95% CI, 0.75-0.98]) was observed. For maternal morbidity, the comparative rates were 2.6% vs 2.9%, respectively, and the weighted relative risk was 0.90 (95% CI, 0.68-1.19). No differences were observed with respect to major congenital malformations overall, low birth weight, preterm birth, respiratory symptoms, or cesarean delivery. Results were consistent across sensitivity analyses. Conclusions and Relevance: There were similar and, in some instances, more favorable neonatal and maternal outcomes for pregnancies exposed to buprenorphine combined with naloxone compared with buprenorphine alone. For the outcomes assessed, compared with buprenorphine alone, buprenorphine with naloxone during pregnancy appears to be a safe treatment option. This supports the view that both formulations are reasonable options for the treatment of opioid use disorder in pregnancy, affirming flexibility in collaborative treatment decision-making.

Emulating a Target Trial of Interventions Initiated During Pregnancy with Healthcare Databases: The Example of COVID-19 Vaccination.

BACKGROUND: Observational studies are often the only option to estimate effects of interventions during pregnancy. Causal inference from observational data can be conceptualized as an attempt to emulate a hypothetical pragmatic randomized trial: the target trial. OBJECTIVE: To provide a step-by-step description of how to use healthcare databases to estimate the effects of interventions initiated during pregnancy. As an example, we describe how to specify and emulate a target trial of COVID-19 vaccination during pregnancy, but the framework can be generally applied to point and sustained strategies involving both pharmacologic and non-pharmacologic interventions. METHODS: First, we specify the protocol of a target trial to evaluate the safety and effectiveness of vaccination during pregnancy. Second, we describe how to use observational data to emulate each component of the protocol of the target trial. We propose different target trials for different gestational periods because the outcomes of interest vary by gestational age at exposure. We identify challenges that affect (i) the target trial and thus its observational emulation (censoring and competing events), and (ii) mostly the observational emulation (confounding, immortal time, and measurement biases). CONCLUSION: Some biases may be unavoidable in observational emulations, but others are avoidable. For instance, immortal time bias can be avoided by aligning the start of follow-up with the gestational age at the time of the intervention, as we would do in the target trial. Explicitly emulating target trials at different gestational ages can help reduce bias and improve the interpretability of effect estimates for interventions during pregnancy.

Development and Validation of Algorithms to Estimate Live Birth Gestational Age in Medicaid Analytic eXtract Data.

BACKGROUND: While healthcare utilization data are useful for postmarketing surveillance of drug safety in pregnancy, the start of pregnancy and gestational age at birth are often incompletely recorded or missing. Our objective was to develop and validate a claims-based live birth gestational age algorithm. METHODS: Using the Medicaid Analytic eXtract (MAX) linked to birth certificates in three states, we developed four candidate algorithms based on: preterm codes; preterm or postterm codes; timing of prenatal care; and prediction models - using conventional regression and machine-learning approaches with a broad range of prespecified and empirically selected predictors. We assessed algorithm performance based on mean squared error (MSE) and proportion of pregnancies with estimated gestational age within 1 and 2 weeks of the gold standard, defined as the clinical or obstetric estimate of gestation on the birth certificate. We validated the best-performing algorithms against medical records in a nationwide sample. We quantified misclassification of select drug exposure scenarios due to estimated gestational age as positive predictive value (PPV), sensitivity, and specificity. RESULTS: Among 114,117 eligible pregnancies, the random forest model with all predictors emerged as the best performing algorithm: MSE 1.5; 84.8% within 1 week and 96.3% within 2 weeks, with similar performance in the nationwide validation cohort. For all exposure scenarios, PPVs were >93.8%, sensitivities >94.3%, and specificities >99.4%. CONCLUSIONS: We developed a highly accurate algorithm for estimating gestational age among live births in the nationwide MAX data, further supporting the value of these data for drug safety surveillance in pregnancy. See video abstract at, http://links.lww.com/EDE/B989 .

A prospective cohort study of preconception COVID-19 vaccination and miscarriage.

STUDY QUESTION: To what extent is preconception maternal or paternal coronavirus disease 2019 (COVID-19) vaccination associated with miscarriage incidence? SUMMARY ANSWER: COVID-19 vaccination in either partner at any time before conception is not associated with an increased rate of miscarriage. WHAT IS KNOWN ALREADY: Several observational studies have evaluated the safety of COVID-19 vaccination during pregnancy and found no association with miscarriage, though no study prospectively evaluated the risk of early miscarriage (gestational weeks [GW] <8) in relation to COVID-19 vaccination. Moreover, no study has evaluated the role of preconception vaccination in both male and female partners. STUDY DESIGN, SIZE, DURATION: An Internet-based, prospective preconception cohort study of couples residing in the USA and Canada. We analyzed data from 1815 female participants who conceived during December 2020-November 2022, including 1570 couples with data on male partner vaccination. PARTICIPANTS/MATERIALS, SETTING, METHODS: Eligible female participants were aged 21-45 years and were trying to conceive without use of fertility treatment at enrollment. Female participants completed questionnaires at baseline, every 8 weeks until pregnancy, and during early and late pregnancy; they could also invite their male partners to complete a baseline questionnaire. We collected data on COVID-19 vaccination (brand and date of doses), history of SARS-CoV-2 infection (yes/no and date of positive test), potential confounders (demographic, reproductive, and lifestyle characteristics), and pregnancy status on all questionnaires. Vaccination status was categorized as never (0 doses before conception), ever (≥1 dose before conception), having a full primary sequence before conception, and completing the full primary sequence ≤3 months before conception. These categories were not mutually exclusive. Participants were followed up from their first positive pregnancy test until miscarriage or a censoring event (induced abortion, ectopic pregnancy, loss to follow-up, 20 weeks' gestation), whichever occurred first. We estimated incidence rate ratios (IRRs) for miscarriage and corresponding 95% CIs using Cox proportional hazards models with GW as the time scale. We used propensity score fine stratification weights to adjust for confounding. MAIN RESULTS AND THE ROLE OF CHANCE: Among 1815 eligible female participants, 75% had received at least one dose of a COVID-19 vaccine by the time of conception. Almost one-quarter of pregnancies resulted in miscarriage, and 75% of miscarriages occurred <8 weeks' gestation. The propensity score-weighted IRR comparing female participants who received at least one dose any time before conception versus those who had not been vaccinated was 0.85 (95% CI: 0.63, 1.14). COVID-19 vaccination was not associated with increased risk of either early miscarriage (GW: <8) or late miscarriage (GW: 8-19). There was no indication of an increased risk of miscarriage associated with male partner vaccination (IRR = 0.90; 95% CI: 0.56, 1.44). LIMITATIONS, REASONS FOR CAUTION: The present study relied on self-reported vaccination status and infection history. Thus, there may be some non-differential misclassification of exposure status. While misclassification of miscarriage is also possible, the preconception cohort design and high prevalence of home pregnancy testing in this cohort reduced the potential for under-ascertainment of miscarriage. As in all observational studies, residual or unmeasured confounding is possible. WIDER IMPLICATIONS OF THE FINDINGS: This is the first study to evaluate prospectively the relation between preconception COVID-19 vaccination in both partners and miscarriage, with more complete ascertainment of early miscarriages than earlier studies of vaccination. The findings are informative for individuals planning a pregnancy and their healthcare providers. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Health [R01-HD086742 (PI: L.A.W.); R01-HD105863S1 (PI: L.A.W. and M.L.E.)], the National Institute of Allergy and Infectious Diseases (R03-AI154544; PI: A.K.R.), and the National Science Foundation (NSF-1914792; PI: L.A.W.). The funders had no role in the study design, data collection, analysis and interpretation of data, writing of the report, or the decision to submit the paper for publication. L.A.W. is a fibroid consultant for AbbVie, Inc. She also receives in-kind donations from Swiss Precision Diagnostics (Clearblue home pregnancy tests) and Kindara.com (fertility apps). M.L.E. received consulting fees from Ro, Hannah, Dadi, VSeat, and Underdog, holds stock in Ro, Hannah, Dadi, and Underdog, is a past president of SSMR, and is a board member of SMRU. K.F.H. reports being an investigator on grants to her institution from UCB and Takeda, unrelated to this study. S.H.-D. reports being an investigator on grants to her institution from Takeda, unrelated to this study, and a methods consultant for UCB and Roche for unrelated drugs. The authors report no other relationships or activities that could appear to have influenced the submitted work. TRIAL REGISTRATION NUMBER: N/A.

Accuracy of identifying pediatric acute bacterial sinusitis diagnoses in outpatient claims data.

PURPOSE: Acute bacterial sinusitis is among the most frequent outpatient infections in children and adolescents and is well suited to study in large healthcare utilization databases, but the validity of International Classification of Diseases, 10th Revision (ICD-10) codes together with antibiotic prescriptions to identify cases of acute bacterial sinusitis has not been established. We aimed to evaluate the validity of ICD-10 codes combined with antibiotic prescriptions to identify new diagnoses of acute bacterial sinusitis among pediatric patients evaluated in the outpatient setting. METHODS: Children and adolescents aged 17 years and younger with an outpatient diagnosis of acute sinusitis along with an antibiotic prescription from an ambulatory facility affiliated with the Mass General Brigham health system were identified via a clinical data warehouse. Patients were stratified by age (0-5 years, 6-11 years, and 12-17 years), and 50 cases per age group were randomly sampled. Medical records were independently reviewed by two pediatric infectious diseases physicians to assess for the documentation of a clinician-defined diagnosis of acute bacterial sinusitis. Positive predictive values (PPVs) and 95% confidence intervals (CIs) were calculated. RESULTS: A total of 150 patients were included in the final cohort. Frontal, maxillary, and "unspecified" sinuses accounted for 88% of the diagnoses. The positive predictive value of the algorithm to identify clinician-defined diagnoses of acute bacterial sinusitis was 92% (95% CI 87%, 95%). The PPVs were consistent across age strata. CONCLUSIONS: ICD-10 codes for acute sinusitis, when paired with a same-day antibiotic prescription, have a high positive predictive value among a cohort of pediatric patients, suggesting that they can be used to study new acute bacterial sinusitis diagnoses with claims.

Achieving comparability in glycemic control between antidiabetic treatment strategies in pregnancy when using real world data.

PURPOSE: Healthcare utilization databases often lack information on glycemic control, a key confounder when studying the safety of antidiabetic treatments, since patients with worse control are channeled to second-line agents, in particular insulin, versus first-line agents such as metformin. We evaluated whether adjustment for measured characteristics attains balance in glycemic control when comparing antidiabetic treatment strategies in pregnant women with pregestational type 2 diabetes (T2DM). METHODS: In a US insurance claims database, we identified 3360 women with T2DM pregnant between 2004 and 2015, of whom a subset of 996 had data on hemoglobin A1c (HbA1c ) levels. We selected insulin only as the comparator group and used propensity score (PS)-matching on comorbidities and proxies of diabetes severity, but not on HbA1c , to adjust for confounding. We used standardized differences (st.diff) to assess balance in claims-based covariates and mean HbA1c (% ± SD) in the subset. RESULTS: There were imbalances in claims-based covariates before PS-matching, with smaller differences when both treatment strategies included insulin. After PS-matching, balance was achieved in most claims-based covariates (st.diff <0.1). Mean HbA1c was similar before and after PS-matching when both treatments included insulin (e.g., 7.1 ± 1.5 vs. 7.7 ± 1.8 and 7.1 ± 1.5 vs. 7.5 ± 1.7, respectively, for metformin + insulin vs. insulin only). Differences in mean HbA1c remained after PS-matching when non-insulin treatments were compared to treatments including insulin (e.g., 6.3 ± 1.1 vs. 7.6 ± 1.7 for metformin only vs. insulin only). CONCLUSIONS: Balance in both claims-based characteristics and glycemic control was attained after restricting the population to women with T2DM and comparing treatment strategies indicated for patients with similar diabetes severity. When comparing treatment strategies with versus without insulin, differences in glycemic control persisted after PS-matching even when balance was attained for other measured characteristics.