Maternal age at delivery is increasing in high-income countries, driven by the increasing engagement of women in higher education and career building, improved medical care during pregnancy, and advances in assisted reproduction technology. Older maternal age is associated with a higher prevalence of chronic diseases during pregnancy, which often leads to drug therapy with the possibility of adverse drug events. On the other hand, if the chronic diseases are left untreated, they can increase the risk of adverse materno-fetal outcomes.
Observational research plays a major role when evaluating health aspects during pregnancy and associated materno-fetal outcomes. Main data sources being used include electronic health records, administrative claims databases, registries and prospective cohorts, and survey data.
This thesis aims to contribute to the general understanding of how such observational health databases can be used to study health aspects during pregnancy.
The following three studies, constituting this PhD thesis, confront different research questions in different fields, based on data from different observational data sources, but have a common focus on pregnant women. A summary of the three studies is provided in the following paragraphs.
Study 1 is a review article with the title: A review of the evidence on the risk of congenital malformations and neurodevelopmental disorders in association with antiseizure medications during pregnancy (Marxer et al., 2021, Expert Opinion on Drug Safety). We critically evaluated and summarized current evidence on the risk of congenital malformations (CM) and neurodevelopmental disorders (NDD) in children of women with epilepsy after in utero exposure to different antiseizure medications (ASM). Further, we highlighted characteristics of the main data sources being used to study the safety of ASM during pregnancy and discussed their benefits and drawbacks. Accumulating evidence mainly from (post-marketing) pregnancy and epilepsy registries, prospective cohorts, and large electronic health databases has clearly shown that in utero exposure to valproate is associated with a high risk of CM (11%) and NDD (up to 30-40%) in the child, whereas lamotrigine and levetiracetam seem to be relatively safe. Evidence on the safety of other ASM is less explicit and especially limited for more recently introduced ASM.
Study 2 is a retrospective descriptive study, entitled: Changes in serum creatinine during and after pregnancy in women with or without chronic kidney disease (Marxer et al., 2021, submitted). Previous studies based on data from secondary or tertiary care suggested that kidneys may not sufficiently adapt to physiological changes during pregnancy, which may accelerate progression of chronic kidney disease (CKD). Thus, we described changes in serum creatinine (SCr) levels (proxies for renal filtration) in 14’401 pregnancies of women with or without renal impairment extracted from the UK-based primary care database Clinical Practice Research Datalink (CPRD) GOLD between 2000 and 2019. Baseline estimated glomerular filtration rate (eGFR) between 75-89 ml/min/1.73 m^2 and between 60-74 ml/min/1.73 m^2 were not associated with deterioration of renal filtration during pregnancy. However, potentially prolonged postpartum hyperfiltration in those with a baseline eGFR between 60-74 ml/min/1.73 m^2 requires further investigation. For low eGFR between 15-59 ml/min/1.73 m^2, renal adaptation was present in trimester 1 and 2. Increased median SCr levels may indicate insufficient renal function in trimester 3, but results have to be interpreted cautiously due to small sample size and potentially selective measurements. Besides describing changes in SCr levels, we captured risk factors for CKD (e.g., metabolic or autoimmune diseases). Moreover, we linked the CPRD GOLD data to inpatient hospital data for validation purposes, and to enrich our data with information on materno-fetal outcomes (birth weight, gestational age, and mode of delivery).
Study 3 is an observational cross-sectional study with the title: Recording of chronic diseases and adverse obstetric outcomes during hospitalizations for a delivery in the national Swiss Hospital Medical Statistics dataset between 2012 and 2018 (Marxer et al., 2022, International Journal of Environmental Research and Public Health). The prevalence of chronic diseases during pregnancy and maternal adverse obstetric outcomes in Switzerland has been insufficiently studied but is of great public health relevance. Thus, we conducted a nationwide study (2012-2018) using data from the Swiss Hospital Medical Statistics (MS) dataset evaluating completeness of recording of 23 chronic diseases and 25 maternal adverse obstetric outcomes during 577’220 hospitalizations for a delivery (98.1% of deliveries in Switzerland). Our results suggest that chronic diseases are under-recorded during delivery hospitalizations in the Swiss MS dataset. At least one diagnosis for a chronic disease was recorded during 4.99% of delivery hospitalizations, which is substantially lower compared to a nationwide Danish registry study (15.49% between 2009 and 2013), which used the same disease definition to quantify disease prevalence during pregnancy. Under-recording of chronic diseases may be due to specific coding guidelines and aspects of whether or not a disease generates billable effort to a hospital. On the other hand, comparison of our results to studies from other European (mainly Scandinavian) countries has shown that maternal adverse obstetric outcomes are more completely captured in the MS dataset. However, future studies are needed to confirm their true prevalence.
In summary, the studies presented in this thesis show how valuable observational health databases are in the field of perinatal epidemiology in order to answer research questions of public health relevance. Moreover, this thesis highlights the benefits and drawbacks of different observational databases, and underlines the value of linking data from different observational databases. Finally, this thesis highlights the importance of multi-database and multi-site collaboration among researchers and the application of advanced epidemiological methods in order to accelerate the generation of new evidence on health-related aspects during pregnancy