Enabling pregnant women and their physicians to make informed medication decisions using artificial intelligence

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Abstract

The role of artificial intelligence (AI) in healthcare for pregnant women. To assess the role of AI in women’s health, discover gaps, and discuss the future of AI in maternal health. A systematic review of English articles using EMBASE, PubMed, and SCOPUS. Search terms included pregnancy and AI. Research articles and book chapters were included, while conference papers, editorials and notes were excluded from the review. Included papers focused on pregnancy and AI methods, and pertained to pharmacologic interventions. We identified 376 distinct studies from our queries. A final set of 31 papers were included for the review. Included papers represented a variety of pregnancy concerns and multidisciplinary applications of AI. Few studies relate to pregnancy, AI, and pharmacologics and therefore, we review carefully those studies. External validation of models and techniques described in the studies is limited, impeding on generalizability of the studies. Our review describes how AI has been applied to address maternal health, throughout the pregnancy process: preconception, prenatal, perinatal, and postnatal health concerns. However, there is a lack of research applying AI methods to understand how pharmacologic treatments affect pregnancy. We identify three areas where AI methods could be used to improve our understanding of pharmacological effects of pregnancy, including: (a) obtaining sound and reliable data from clinical records (15 studies), (b) designing optimized animal experiments to validate specific hypotheses (1 study) to (c) implementing decision support systems that inform decision-making (11 studies). The largest literature gap that we identified is with regards to using AI methods to optimize translational studies between animals and humans for pregnancy-related drug exposures.

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Most cited references 63

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Epidemiology of pre-eclampsia and the other hypertensive disorders of pregnancy.

Jennifer A Hutcheon, Sarka Lisonkova, K.S. Joseph (2011)

Hypertensive disorders of pregnancy include chronic hypertension, gestational hypertension, pre-eclampsia and chronic hypertension with superimposed pre-eclampsia. Pre-eclampsia complicates about 3% of pregnancies, and all hypertensive disorders affect about five to 10% of pregnancies. Secular increases in chronic hypertension, gestational hypertension and pre-eclampsia have occurred as a result of changes in maternal characteristics (such as maternal age and pre-pregnancy weight), whereas declines in eclampsia have followed widespread antenatal care and use of prophylactic treatments (such as magnesium sulphate). Determinants of pre-eclampsia rates include a bewildering array of risk and protective factors, including familial factors, sperm exposure, maternal smoking, pre-existing medical conditions (such as hypertension, diabetes mellitus and anti-phospholipid syndrome), and miscellaneous ones such as plurality, older maternal age and obesity. Hypertensive disorders are associated with higher rates of maternal, fetal and infant mortality, and severe morbidity, especially in cases of severe pre-eclampsia, eclampsia and haemolysis, elevated liver enzymes and low platelets syndrome. Copyright © 2011 Elsevier Ltd. All rights reserved.

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Gestational Diabetes Mellitus and Macrosomia: A Literature Review

Kamana Kc, Sumisti Shakya, Hua Zhang (2015)

Background: Fetal macrosomia, defined as a birth weight ≥4,000 g, may affect 12% of newborns of normal women and 15-45% of newborns of women with gestational diabetes mellitus (GDM). The increased risk of macrosomia in GDM is mainly due to the increased insulin resistance of the mother. In GDM, a higher amount of blood glucose passes through the placenta into the fetal circulation. As a result, extra glucose in the fetus is stored as body fat causing macrosomia, which is also called ‘large for gestational age'. This paper reviews studies that explored the impact of GDM and fetal macrosomia as well as macrosomia-related complications on birth outcomes and offers an evaluation of maternal and fetal health. Summary: Fetal macrosomia is a common adverse infant outcome of GDM if unrecognized and untreated in time. For the infant, macrosomia increases the risk of shoulder dystocia, clavicle fractures and brachial plexus injury and increases the rate of admissions to the neonatal intensive care unit. For the mother, the risks associated with macrosomia are cesarean delivery, postpartum hemorrhage and vaginal lacerations. Infants of women with GDM are at an increased risk of becoming overweight or obese at a young age (during adolescence) and are more likely to develop type II diabetes later in life. Besides, the findings of several studies that epigenetic alterations of different genes of the fetus of a GDM mother in utero could result in the transgenerational transmission of GDM and type II diabetes are of concern.

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High prevalence of type 2 diabetes and pre-diabetes in adult offspring of women with gestational diabetes mellitus or type 1 diabetes: the role of intrauterine hyperglycemia.

Tine D. Clausen, Elisabeth Mathiesen, Torben Hansen … (2008)

The role of intrauterine hyperglycemia and future risk of type 2 diabetes in human offspring is debated. We studied glucose tolerance in adult offspring of women with either gestational diabetes mellitus (GDM) or type 1 diabetes, taking the impact of both intrauterine hyperglycemia and genetic predisposition to type 2 diabetes into account. The glucose tolerance status following a 2-h 75-g oral glucose tolerance test (OGTT) was evaluated in 597 subjects, primarily Caucasians, aged 18-27 years. They were subdivided into four groups according to maternal glucose metabolism during pregnancy and genetic predisposition to type 2 diabetes: 1) offspring of women with diet-treated GDM (O-GDM), 2) offspring of genetically predisposed women with a normal OGTT (O-NoGDM), 3) offspring of women with type 1 diabetes (O-type 1), and 4) offspring of women from the background population (O-BP). The prevalence of type 2 diabetes and pre-diabetes (impaired glucose tolerance or impaired fasting glucose) in the four groups was 21, 12, 11, and 4%, respectively. In multiple logistic regression analysis, the adjusted odds ratios (ORs) for type 2 diabetes/pre-diabetes were 7.76 (95% CI 2.58-23.39) in O-GDM and 4.02 (1.31-12.33) in O-type 1 compared with O-BP. In O-type 1, the risk of type 2 diabetes/pre-diabetes was significantly associated with elevated maternal blood glucose in late pregnancy: OR 1.41 (1.04-1.91) per mmol/l. A hyperglycemic intrauterine environment appears to be involved in the pathogenesis of type 2 diabetes/pre-diabetes in adult offspring of primarily Caucasian women with either diet-treated GDM or type 1 diabetes during pregnancy.

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Author and article information

Contributors

Mary Regina Boland:

ORCID: http://orcid.org/0000-0001-8576-6408

bolandm@upenn.edu

Journal

Journal ID (nlm-ta): J Pharmacokinet Pharmacodyn

Journal ID (iso-abbrev): J Pharmacokinet Pharmacodyn

Title: Journal of Pharmacokinetics and Pharmacodynamics

Publisher: Springer US (New York )

ISSN (Print): 1567-567X

ISSN (Electronic): 1573-8744

Publication date (Electronic): 11 April 2020

Publication date PMC-release: 11 April 2020

Publication date (Print): 2020

Volume: 47

Issue: 4

Pages: 305-318

Affiliations

[1 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, , University of Pennsylvania, ; 423 Guardian Drive, 421 Blockley Hall, Philadelphia, PA 19104 USA

[2 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Institute for Biomedical Informatics, , University of Pennsylvania, ; Philadelphia, USA

[3 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Center for Excellence in Environmental Toxicology, , University of Pennsylvania, ; Philadelphia, USA

[4 ]GRID grid.239552.a, ISNI 0000 0001 0680 8770, Department of Biomedical and Health Informatics, , Children’s Hospital of Philadelphia, ; Philadelphia, USA

Author information

Mary Regina Boland http://orcid.org/0000-0001-8576-6408

Article

Publisher ID: 9685

DOI: 10.1007/s10928-020-09685-1

PMC ID: 7473961

PubMed ID: 32279157

SO-VID: cd9d8f0c-f019-453f-a9b4-13b3cde7b0c2

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Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 11 February 2020

Date accepted : 2 April 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100007928, Perelman School of Medicine, University of Pennsylvania;

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ScienceOpen disciplines: Pharmacology & Pharmaceutical medicine

Keywords: literature review,pregnancy,artificial intelligence,machine learning,decision support systems

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ScienceOpen disciplines: Pharmacology & Pharmaceutical medicine

Keywords: literature review, pregnancy, artificial intelligence, machine learning, decision support systems

Enabling pregnant women and their physicians to make informed medication decisions using artificial intelligence

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Artificial Intelligence in Medicine

Most cited references 63

Epidemiology of pre-eclampsia and the other hypertensive disorders of pregnancy.

Gestational Diabetes Mellitus and Macrosomia: A Literature Review

High prevalence of type 2 diabetes and pre-diabetes in adult offspring of women with gestational diabetes mellitus or type 1 diabetes: the role of intrauterine hyperglycemia.

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