Evidence map›Paper›PMID 37621193›Full record

ArticleBirth defects research2023

Teratology research in the shadow of the Dobbs decision.

Anne Drapkin Lyerly

Open access · bronzeAbstract read
In one paragraph

Article in Birth defects research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 80% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Anne Drapkin LyerlyUniversity of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-2211-6920
University of North Carolina at Chapel Hill · US

Funding

The PHASES Project: Pregnancy and HIV/AIDS-Seeking Equitable StudyR01AI108368 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAY, SUZANNE LOUISE, LYERLY, ANNE DRAPKIN · 2015 to 2024
$6.4M
NIAID NIH HHS R01 AI108368
6 · The paper itself

Abstract

Following the 2022 US Supreme Court decision in Dobbs vs. Jackson Women's Health Organization, numerous states have passed laws banning or severely restricting abortion. The consequences of the decision stretch beyond abortion contexts, including progress on developing a more robust evidence base for care in pregnancy. In this Robert L. Brent lecture, I explore the impact of the Dobbs decision on teratology research, arguing that it is of importance even and perhaps especially for those concerned about the moral complexities of ending a pregnancy. For as abortion restrictions threaten teratology research, they also threaten its life-affirming aims. First, I show how teratology research and abortion are intertwined, highlighting the stories of Sherri Finkbine and Frances Kelsey, two courageous women whose lives intersected with both. Second, I describe how restrictions on abortion make teratology research more difficult and ethically complex, highlighting additional risks to research participants and staff, as well as new challenges to scientific validity and feasibility. And third, foregrounding yet another story of courage (and heartbreak), I highlight how abortion restrictions make teratology research more important than ever. Honoring Dr. Brent's legacy requires addressing-rather than avoiding-the ethical challenges of pregnancy-related research, especially now in the post-Dobbs era.

Indexed as

Abortion, InducedTeratologyFemaleHumansPregnancyabortionbirth defectsethicsFrances KelseypregnancySherri Finkbinethalidomide

Identifiers

PMID37621193
PMCPMC10528897
OpenAlexW4386151778

What OpenQuestion 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 OpenQuestion graph.