Evidence map›Paper›PMID 40451450›Full record

ArticleAmerican journal of obstetrics and gynecology2025

Sickle cell trait and severe maternal morbidity.

Nansi S Boghossian, Lucy T Greenberg, Ciaran S Phibbs, George R Saade, Jeannette Rogowski, Molly Passarella, Jeffrey S Buzas, Scott A Lorch

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of obstetrics and gynecology, 2025. 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
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.

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

8 authors.

Nansi S BoghossianDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC. Electronic address: nboghoss@mailbox.sc.edu.
Lucy T GreenbergVermont Oxford Network, Burlington, VT.
Ciaran S PhibbsHealth Economics Resource Center and Center for Implementation to Innovation, Veterans Affairs Palo Alto Health Care System, Menlo Park, CA; Department of Pediatrics, Division of Neonatology, Stanford University School of Medicine, Stanford, CA.
George R SaadeDepartment of Obstetrics & Gynecology, Eastern Virginia Medical School, Norfolk, VA.
Jeannette RogowskiDepartment of Health Policy and Administration, The Pennsylvania State University, State College, PA.
Molly PassarellaRoberts Center for Pediatric Research, Children's Hospital of Philadelphia, Philadelphia, PA.
Jeffrey S BuzasDepartment of Mathematics and Statistics, University of Vermont, Burlington, VT.
Scott A LorchRoberts Center for Pediatric Research, Children's Hospital of Philadelphia, Philadelphia, PA; Leonard Davis Institute of Health Economics, Wharton School, University of Pennsylvania, Philadelphia, PA.

Funding

Hospital quality, Medicaid expansion, and racial/ethnic disparitiesin maternal mortality and morbidityR01MD016012 · NIMHD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BOGHOSSIAN, NANSI · 2020 to 2024
$3.2M
Obstetric delivery volume, regionalization, and maternal and infant outcomesR01HD099197 · NICHD · STANFORD UNIVERSITY · PI PHIBBS, CIARAN S. · 2020 to 2023
$2.7M
Effect of Changing NICU Patient Volumes and Levels of Care on Neonatal OutcomesR01HD084819 · NICHD · STANFORD UNIVERSITY · PI LORCH, SCOTT A, PHIBBS, CIARAN S. · 2016 to 2018
$1.1M
NICHD NIH HHS R01 HD084819NICHD NIH HHS R01 HD099197NIMHD NIH HHS R01 MD016012
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

air and thrombotic embolismblood transfusionsevere maternal morbiditysickle cell trait

Identifiers

PMID40451450
PMCPMC12536498

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.