The evidence gap relating to the risk of congenital anomalies (CA) associated with first trimester medication exposure in pregnancy is well recognised. We describe the EUROmediCAT network and databases, and the methodological approach to pregnancy pharmacovigilance. Multidisciplinary expertise includes congenital anomaly diagnosis and epidemiology, pharmacoepidemiology, pharmacology and teratology. The EUROmediCAT central database comprises standardised data from 19 EUROCAT CA registries in 14 countries, including more than 40,000 CA cases 1995-2021 with first trimester medication exposure data recorded, and a population coverage of 14.6 million births, growing by more than 650,000 births per year. The distributed database enables federated data analysis across eight countries which can link CA registries to electronic healthcare data, with population coverage of up to 917,000 births per year for linkage to maternal prescriptions, of which 315,000 births per year for linkage also to data on all births. The databases have enabled a variety of study designs: case-malformed control studies, cohort studies, disease cohort studies, signal detection studies, prevalence and ecological studies, and medication utilisation studies. A key strength is that studies of CA risk can address accurately the specificity of risk by type of CA. EUROmediCAT presents a unique data and expert resource for tackling the enormous evidence gap regarding the safety of medication during pregnancy.

Objective: We examined the possible impact of selective serotonin reuptake inhibitor (SSRI)-trajectories describing the timing of different SSRI dosages on adverse neonatal outcomes. Design: Longitudinal register study Setting: Population based study from Kuopio University Hospital Birth Register. Population or Sample: Altogether 508 mothers who reported using SSRIs in pregnancy, where matched to a five-fold comparison group (n=2540), based on maternal depression, psychiatric diagnoses and age. Methods: We applied unsupervised k-Means longitudinal clustering method to identify four distinct patterns of SSRI use, and propensity score adjusted generalized estimating equations to examine the associations between the exposure groups and the neonatal outcomes, using the unexposed group as reference. Main Outcome Measures: Birth weight, placenta weight, placenta-to-birth-weight ratio (PBWR), umbilical cord length, gestational length, premature birth, low 5-min Apgar score, neonatal intensive care unit (NICU) admission. Results: Compared to the no SSRI group, we found no associations between the use of SSRI up to standard doses and the neonatal outcomes. However, the sustained high dose group (~twice the standard dose) displayed significantly higher mean PBWR (B=1.65, 95% CI=0.83, 2.47). In addition, the odds of low Apgar score for the high dose group were about 3.2-fold (OR=3.2; 95%CI=1.04, 9.79), and the odds of NICU admission 2.6-fold (OR=2.6; 95%CI=1.10,6.03), compared with no SSRI group. Conclusions: Sustained, increasing, or decreasing use of SSRI up to standard doses were not associated with adverse neonatal outcomes. However, caution is advised as sustained higher doses may be linked to reduced placental efficacy and higher risk of adverse neonatal health.

Purpose. In 2019, the Innovative Medicines Initiative funded the ConcePTION project to enhance monitoring of medication safety in pregnancy and breastfeeding. This paper describes how the ConcePTION Pregnancy Algorithm (PA) identified pregnancies in 10 diverse European electronic healthcare data sources and estimated their duration. Methods. Data sources from six European countries were mapped to the ConcePTION Common Data Model. Any pregnancy-related record was retrieved from various available data banks, including birth register, primary care records, and hospital records, and reconciled into episodes of pregnancy (starting between 01/2015 and 12/2019), each with start date, end date, and type of end. A random forest model was used to estimate missing gestational ages for incomplete records. Parameters were tailored to data sources to address local variations in data availability, collection, and governance. Model performance was evaluated using cross-validated Root Mean Squared Error (RMSE). Results. The PA identified ~ 2.7 million pregnancies, in over 2.2 million individuals. Most ended in live births (50%-83%), 1%-15% in elective terminations, and 4%-10% in spontaneous abortions, depending on data sources. Pregnancies with unknown type of end were also retrieved (2%-34%). Gestational age was predicted for 6%-89% of records (RMSE: 17-50 days). The median gestational age at first identified pregnancy record ranged from 47 to 280 days. Conclusions. We developed an open-source algorithm to identify and date pregnancies, including early-stage pregnancies with unknown end and/or ongoing at the time of data extraction. This algorithm may facilitate multinational studies, improving generation of timely real-world evidence about use and safety of medicinal products in pregnancy.

Purpose Pregnancies ending before gestational week 12 are common but not notified to the Medical Birth Registry of Norway. Our goal was to develop an algorithm that more completely detects and dates pregnancy outcomes by using diagnostic codes from primary and secondary care registries to complement information from the birth registry. Methods We used nationwide linked registry data between 2008 and 2018 in a hierarchical manner: We developed an algorithm to arrive at unique pregnancy outcomes, considering codes within 56 days as the same event. To infer gestational age of pregnancy outcomes before gestational week 12, we used the median gestational week of pregnancy markers (45 ICD-10 codes and 9 ICPC-2 codes). When no pregnancy markers were available, we assigned outcome-specific gestational age estimates. The performance of the algorithm was assessed by blinded clinicians. Results Using only the medical birth registry, we identified 649,703 pregnancies, including 1,369 (0.2%) miscarriages and 3,058 (0.5%) elective terminations. With the new algorithm, we detected 859,449 pregnancies, including 642,712 live-births (74.8%), 112,257 miscarriages (13.1%), 94,664 elective terminations (11.0%), 6,429 ectopic pregnancies (0.7%), 2,564 stillbirths (0.3%), and 823 molar pregnancies (0.1%). The median gestational age was 10 +0 weeks (IQR 10 +0-11 +3) for miscarriages and 8 +0 weeks (IQR 8 +0-9 +6) for elective terminations. Gestational age could be inferred using pregnancy markers for 66.3% of miscarriages and 47.2% of elective terminations. Conclusion The pregnancy algorithm improved the detection and dating of early non-live pregnancy outcomes that would have gone unnoticed if relying solely on the medical birth registry information.

Objective: To quantify the association between prenatal exposure to selective serotonin (SSRI) and serotonin-norepinephrine (SNRI) reuptake inhibitor antidepressants and ADHD in offspring, with quantification of exposure misclassification bias. Design: Norwegian Mother, Father and Child Cohort Study (MoBa), linked to national health registries. Setting: Norway. Population: 6395 children born to women who self-reported depression/anxiety in pregnancy and were either medicated with SSRI/SNRI in pregnancy (n=818) or non-medicated (n=5228), or did not report depression/anxiety but used antidepressants six months prior to pregnancy (discontinuers, n=349). Main outcome measure: Diagnosis of ADHD or redeemed prescription for ADHD medication in children, and mother-reported symptoms of ADHD at child age five years. Results: When the hazard was averaged over the duration of the study’s follow-up, there was no difference in ADHD risk between ever in-utero SSRI/SNRI-exposed children and comparators (weighted Hazard Ratio (wHR): 1.07, 95% Confidence Interval (CI): 0.76-1.51, vs. non-medicated; wHR: 1.53, 95% CI: 0.77-3.07, vs. discontinuers). Underestimation of effects due to exposure misclassification was modest. At early childhood, the risk for ADHD was lower with prenatal SSRI/SNRI exposure compared with non-medicated, and so were ADHD symptoms (weighted β: -0.23, 95% CI: -0.39, -0.08); this risk became elevated at child age 7-9 years (wHR: 1.93, 95% CI: 1.22-3.05). Maternal depression/anxiety prior to pregnancy was independently associated with child ADHD. Conclusion: Prenatal SSRI/SNRI exposure is unlikely to considerably increase the risk of child ADHD beyond that posed by the underlying psychiatric illness. The elevated risk at child age 7-9 years needs to be further elucidated.