Use of medication in pregnancy on the rise: Study on 1.4 million Danish pregnancies from 1998 to 2018.

INTRODUCTION: Maternal demographics have evolved, and more women than ever enter pregnancy with preexisting comorbidity and with potentially complex medication exposure, including polypharmacy (concomitant intake of multiple medications). This study aims to describe the evolution of medication use in pregnancy in Denmark from 1998 to 2018 with special focus on polypharmacy, patterns of use, and underlying demographics. MATERIAL AND METHODS: A Danish nationwide historical registry study based on all clinically recognized pregnancies with a gestation ≥10 weeks between 1998 and 2018. Medication use was estimated by redemption of prescriptions during pregnancy. RESULTS: Among a total of 1 402 327 clinically recognized pregnancies, redemption of at least one prescription medication during pregnancy increased from 56.9% in 1998 to 63.3% in 2018, coinciding with an increased use of polypharmacy (from 24.8% in 1998 to 35.2% in 2018). The prevalence of pregnant women who used medications for chronic conditions increased more than the prevalence of women treated for occasional or short-time conditions. Redemption of one or multiple prescription medications during pregnancy was mostly seen among pregnant women ≥35 years of age. However, pregnant women <25 years old exhibited the largest increase in medication use during the study period. CONCLUSIONS: Medication use in general, and polypharmacy in particular, increased from 1998 to 2008, possibly as the result of an increased prevalence of pregnant women with chronic conditions requiring pharmacological treatment. Notably, a marked maternal age-based discrepancy in usage pattern was observed, highlighting the need for further research in this area. The rise in the prevalence of polypharmacy during pregnancy underscores the need for pharmacovigilance to monitor adverse effects. Future studies should investigate the patterns of polypharmacy and the accompanying maternal and fetal risks.

Polypharmacy in polymorbid pregnancies and the risk of congenital malformations-A systematic review.

With an increased prevalence of concurrent morbidities during pregnancy, polypharmacy has become increasingly common in pregnant women. The risks associated with polypharmacy may exceed those of individual medication because of drug-drug interactions. This systematic review aims to evaluate the risk of congenital malformations in polymorbid pregnancies exposed to first-trimester polypharmacy. PubMed, Embase and Scopus were searched to identify original human studies with first- trimester polypharmacy due to polymorbidity as the exposure and congenital malformations as the outcome. After screening of 4034 identified records, seven studies fulfilled the inclusion criteria. Four of the seven studies reported an increased risk of congenital malformations compared with unexposed or monotherapy, odds ratios ranging from 1.1 to >10.0. Particularly, short-term anti-infective treatment combined with other drugs and P-glycoprotein substrates were associated with increased malformation risks. In conclusion, knowledge is limited on risks associated with first-trimester polypharmacy due to polymorbidity with the underlying evidence of low quantity and quality. Therefore, an increased focus on pharmacovigilance to enable safe drug use in early pregnancy is needed. Large-scale register-based studies and better knowledge of placental biology are needed to support the clinical management of polymorbid pregnancies that require polypharmacy.

Transfer learning for non-image data in clinical research: A scoping review.

BACKGROUND: Transfer learning is a form of machine learning where a pre-trained model trained on a specific task is reused as a starting point and tailored to another task in a different dataset. While transfer learning has garnered considerable attention in medical image analysis, its use for clinical non-image data is not well studied. Therefore, the objective of this scoping review was to explore the use of transfer learning for non-image data in the clinical literature. METHODS AND FINDINGS: We systematically searched medical databases (PubMed, EMBASE, CINAHL) for peer-reviewed clinical studies that used transfer learning on human non-image data. We included 83 studies in the review. More than half of the studies (63%) were published within 12 months of the search. Transfer learning was most often applied to time series data (61%), followed by tabular data (18%), audio (12%) and text (8%). Thirty-three (40%) studies applied an image-based model to non-image data after transforming data into images (e.g. spectrograms). Twenty-nine (35%) studies did not have any authors with a health-related affiliation. Many studies used publicly available datasets (66%) and models (49%), but fewer shared their code (27%). CONCLUSIONS: In this scoping review, we have described current trends in the use of transfer learning for non-image data in the clinical literature. We found that the use of transfer learning has grown rapidly within the last few years. We have identified studies and demonstrated the potential of transfer learning in clinical research in a wide range of medical specialties. More interdisciplinary collaborations and the wider adaption of reproducible research principles are needed to increase the impact of transfer learning in clinical research.

Postpartum placental CT angiography in normal pregnancies and in those complicated by diabetes mellitus.

INTRODUCTION: Pregnancy complicated by diabetes mellitus (DM) is a central obstetric problem often complicated by fetal macrosomia and increased risk of intrapartum asphyxia. This risk might be explained by fetoplacental vascular abnormalities. This study aimed to investigate the fetoplacental vascular volume by placental CT angiography in normal pregnancies and in pregnancies complicated by type 1 DM (T1DM), diet controlled gestational DM (GDMd), and insulin treated gestational DM (GDMi). METHODS: Postpartum, barium contrast enhanced placental CT angiography was performed in 27 normal pregnancies and 25 DM pregnancies (8 T1DM, 8 GDMd, and 9 GDMi). The fetoplacental vascular volume/placenta weight (FVV/PW)-ratio and fetoplacental vascular volume/birth weight (FVV/BW)-ratio of each diabetic group were compared to the normal group with multiple regression analysis adjusted for GA. In all pregnancies a standardized histopathological placental examination was performed postpartum. RESULTS: In normal pregnancies, the fetoplacental vascular volume increased with GA (p < 0.001), placental weight (p < 0.001), and birth weight (p < 0.001). In T1DM and GDMi pregnancies, the gestational age adjusted placental weight and the birth weight were increased when compared to normal pregnancies (p < 0.05). The FVV/BW-ratio was significantly reduced in both T1DM and GDMi pregnancies when compared to normal pregnancies (p = 0.003 and p = 0.009, respectively). DISCUSSION: This study demonstrates, that in insulin treated DM pregnancies the fetus as well as the placenta is larger than normal. However, despite a large placenta, a relatively smaller fetoplacental vascular volume supplies the macrosomic fetus. This finding might explain why fetuses from insulin treated DM pregnancies have high vulnerability to intrauterine and intrapartum asphyxia.