Evidence map›Paper›PMID 31433567›Full record

ArticleBirth defects research2019

Data-driven queries between medications and spontaneous preterm birth among 2.5 million pregnancies.

Ivana Marić, Virginia D Winn, Evgeniya Borisenko, Kari A Weber, Ronald J Wong, Natali Aziz, Yair J Blumenfeld, Yasser Y El-Sayed, David K Stevenson, Gary M Shaw

Open access · greenAbstract read
In one paragraph

Article in Birth defects research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
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

13 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. PregMedNet: Multifaceted Maternal Medication Impacts on Neonatal Complications.medRxiv : the preprint server for health sciences · 2025
    Article
  3. Article
  4. Article
  5. Hydroxychloroquine in Lupus Pregnancy and Risk of Preeclampsia.Arthritis & rheumatology (Hoboken, N.J.) · 2024
    Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Ivana MarićDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California.ORCID 0000-0002-9441-521X
Virginia D WinnDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.
Evgeniya BorisenkoSchool of Engineering, Stanford University, Stanford, California.
Kari A WeberDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California.ORCID 0000-0001-5138-7389
Ronald J WongDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California.
Natali AzizDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.
Yair J BlumenfeldDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.
Yasser Y El-SayedDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.
David K StevensonDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California.
Gary M ShawDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California.ORCID 0000-0001-7438-4914
Stanford University · US

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
NCATS NIH HHS UL1 TR001085NCATS NIH HHS UL1 TR003142
6 · The paper itself

Abstract

backgroundOur goal was to develop an approach that can systematically identify potential associations between medication prescribed in pregnancy and spontaneous preterm birth (sPTB) by mining large administrative "claims" databases containing hundreds of medications. One such association that we illustrate emerged with antiviral medications used for herpes treatment.

methodsIBM MarketScan® databases (2007-2016) were used. A pregnancy cohort was established using International Classification of Diseases (ICD-9/10) codes. Multiple hypothesis testing and the Benjamini-Hochberg procedure that limited false discovery rate at 5% revealed, among 863 medications, five that showed odds ratios (ORs) <1. The statistically strongest was an association between antivirals and sPTB that we illustrate as a real example of our approach, specifically for treatment of genital herpes (GH). Three groups of women were identified based on diagnosis of GH and treatment during the first 36 weeks of pregnancy: (a) GH without treatment; (b) GH treated with antivirals; (c) no GH or treatment.

resultsWe identified 2,538,255 deliveries. 0.98% women had a diagnosis of GH. Among them, 60.0% received antiviral treatment. Women with treated GH had OR < 1, (OR [95% CI] = 0.91 [0.85, 0.98]). In contrast, women with untreated GH had a small increased risk of sPTB (OR [95% CI] =1.22 [1.14, 1.32]).

conclusionsData-driven approaches can effectively generate new hypotheses on associations between medications and sPTB. This analysis led us to examine the association with GH treatment. While unknown confounders may impact these findings, our results indicate that women with untreated GH have a modest increased risk of sPTB.

Indexed as

Cohort StudiesDatabases, FactualFemaleGestational AgeHerpes GenitalisHumansInfant, NewbornMalePregnancyPremature BirthPrescription DrugsRisk FactorsPrescription Drugsadministrative claims databasesdata mininggenital herpesmultiple hypothesis testingpreterm birth

Identifiers

PMID31433567
PMCPMC11199711
OpenAlexW2969676387

What Socratic holds

Textmetadata
LicenceTDM
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.