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.

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.

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.

Perinatal Outcomes Associated With Metformin Use During Pregnancy in Women With Pregestational Type 2 Diabetes Mellitus.

OBJECTIVE: We emulated a modified randomized trial (Metformin in Women With Type 2 Diabetes in Pregnancy [MiTy]) to compare the perinatal outcomes in women continuing versus discontinuing metformin during pregnancy among those with type 2 diabetes treated with metformin plus insulin before pregnancy. RESEARCH DESIGN AND METHODS: This study used two health care claims databases (U.S., 2000-2020). Pregnant women age 18-45 years with type 2 diabetes who were treated with metformin plus insulin at conception were eligible. The primary outcome was a composite of preterm birth, birth injury, neonatal respiratory distress, neonatal hypoglycemia, and neonatal intensive care unit admission. Secondary outcomes included the components of the primary composite outcome, gestational hypertension, preeclampsia, maternal hypoglycemia, cesarean delivery, infants large for gestational age, infants small for gestational age (SGA), sepsis, and hyperbilirubinemia. We adjusted for potential baseline confounders, including demographic characteristics, comorbidities, and proxies for diabetes progression. RESULTS: Of 2,983 eligible patients, 72% discontinued use of metformin during pregnancy. The average age at conception was 32 years, and the prevalence of several comorbidities was higher among continuers. The risk of the composite outcome was 46% for continuers and 48% for discontinuers. The adjusted risk ratio was 0.92 (95% CI 0.81, 1.03). Risks were similar between treatments and consistent between databases for most secondary outcomes, except for SGA, which was elevated in continuers only in the commercially insured population. CONCLUSIONS: Our findings were consistent with those reported in the MiTy randomized trial. Continuing metformin during pregnancy was not associated with increased risk of a neonatal composite adverse outcome. However, a possible metformin-associated risk of SGA warrants further consideration.

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 U.S. Food and Drug Administration 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. As 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.

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.

Automated Identification of Fall-related Injuries in Unstructured Clinical Notes.

Fall-related injuries (FRIs) are a major cause of hospitalizations among older patients, but identifying them in unstructured clinical notes poses challenges for large-scale research. In this study, we developed and evaluated Natural Language Processing (NLP) models to address this issue. We utilized all available clinical notes from the Mass General Brigham for 2,100 older adults, identifying 154,949 paragraphs of interest through automatic scanning for FRI-related keywords. Two clinical experts directly labeled 5,000 paragraphs to generate benchmark-standard labels, while 3,689 validated patterns were annotated, indirectly labeling 93,157 paragraphs as validated-standard labels. Five NLP models, including vanilla BERT, RoBERTa, Clinical-BERT, Distil-BERT, and SVM, were trained using 2,000 benchmark paragraphs and all validated paragraphs. BERT-based models were trained in three stages: Masked Language Modeling, General Boolean Question Answering (QA), and QA for FRI. For validation, 500 benchmark paragraphs were used, and the remaining 2,500 for testing. Performance metrics (precision, recall, F1 scores, Area Under ROC [AUROC] or Precision-Recall [AUPR] curves) were employed by comparison, with RoBERTa showing the best performance. Precision was 0.90 [0.88-0.91], recall [0.90-0.93], F1 score 0.90 [0.89-0.92], AUROC and AUPR curves of 0.96 [0.95-0.97]. These NLP models accurately identify FRIs from unstructured clinical notes, potentially enhancing clinical notes-based research efficiency.

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.

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.

First-trimester exposure to newer antiretroviral agents and congenital anomalies in a US 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 antiretrovirals (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% confidence interval (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.

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.

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.

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 [RR pooled : 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 (RR pooled : 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.

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.

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.).