Evidence map›Paper›PMID 42431892›Full record

ArticleNature communications2026

PregMedNet: Multifaceted maternal medication impacts on neonatal complications.

Yeasul Kim, Ivana Marić, Chloe M Kashiwagi, Lichy Han, Philip Chung, Jonathan D Reiss, Lindsay D Butcher, Kaitlin J Caoili, Eloïse Berson, Lei Xue and 21 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

31 authors.

Yeasul KimDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA. ykim824@stanford.edu.ORCID http://orcid.org/0000-0001-8289-1297
Ivana MarićDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-9441-521X
Chloe M KashiwagiDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
Lichy HanDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-5785-0968
Philip ChungDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-1194-7510
Jonathan D ReissDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1460-8570
Lindsay D ButcherDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0009-0006-9353-2795
Kaitlin J CaoiliDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
Eloïse BersonMines Paris, PSL Research University, CBIO-Centre for Computational Biology, Paris, France.ORCID http://orcid.org/0000-0003-1046-125X
Lei XueDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
Camilo EspinosaDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1630-1564
Tomin JamesDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
Sayane ShomeDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
Feng XieDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-0215-667X
Marc GhanemDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
David SeongDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-8980-5731
Alan L ChangDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1716-0134
S Momsen ReinckeDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
Samson MatarasoDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-3146-2243
Chi-Hung ShuDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0009-0009-3486-8856
Davide De FrancescoDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
Martin BeckerDepartment of Mathematics and Computer Science, Philipps-Universität Marburg, Marburg, Germany.
Wasan M KumarMedical Doctor Program, Stanford University School of Medicine, Stanford, CA, USA.
Ronald J WongDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1205-6936
Brice GaudilliereDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-3475-5706
Martin S AngstDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-1550-8136
Gary M ShawDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
Brian T BatemanDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA.
David K StevensonDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-7127-0281
Lawrence S PrinceDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
Nima AghaeepourDepartment of Anesthesiology, Perioperative, and Pain Medicine, Stanford School of Medicine, Stanford, CA, USA. naghaeep@stanford.edu.ORCID http://orcid.org/0000-0002-6117-8764

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Machine Learning for Integrative Modeling of the Immune System in Clinical SettingsR35GM138353 · NIGMS · STANFORD UNIVERSITY · PI AGHAEEPOUR, NIMA · 2020 to 2024
$2.2M
Burroughs Wellcome Fund (BWF) 1019816NCATS NIH HHS UL1 TR003142NIGMS NIH HHS R35 GM138353U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R35GM138353
6 · The paper itself

Abstract

While medication use is common among pregnant women, medication safety remains insufficiently characterized because studies in pregnant women are challenging due to safety concerns. The recent digitization of healthcare databases and advances in computational methods have created new opportunities for large-scale, retrospective drug safety evaluations. Here, we present PregMedNet, a platform that characterizes multifaceted maternal medication associations on neonatal outcomes during pregnancy, covering more than 27,000 drug-disease pairs across 1,152 medications and 24 outcomes. These results encompass known and additional odds ratios (ORs), adjusted ORs, and drug-drug interactions, systematically analyzed using nationwide claims data and an advanced machine learning pipeline. Notably, one of the associations identified in this study is supported by in vivo experiments, increasing confidence in PregMedNet's findings and highlighting the utility of claims data and machine learning for perinatal medication safety studies. Additionally, potential biological mechanisms underlying the associations are explored using a graph learning method, providing candidate pathways for future mechanistic investigations. We expect that PregMedNet will contribute to advancing maternal medication safety and improving neonatal outcomes by providing extensive, multifaceted drug safety information on this previously underrepresented population.

Indexed as

Drug-Related Side Effects and Adverse ReactionsPregnancy ComplicationsDatabases, FactualDrug InteractionsFemaleHumansInfant, NewbornMachine LearningPregnancyPregnancy OutcomeRetrospective Studies

Identifiers

PMID42431892
PMCPMC13483950

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.