Evidence map›Paper›PMID 37489421›Full record

ArticleClinics and practice2023

Firearm Injuries during Pregnancy in the USA.

Taylor Luster, Randall T Loder

Open access · goldAbstract read
In one paragraph

Article in Clinics and practice, 2023. 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
0.8field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

2 authors at 2 institutions in 1 country.

Taylor LusterDivision of Student Affairs, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Randall T LoderDepartment of Orthopaedic Surgery, Riley Children's Hospital, Indiana University School of Medicine, Indianapolis, IN 46202, USA.ORCID 0000-0003-1217-0528
Indiana University School of MedicineRiley Hospital for Children · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trauma during pregnancy is the leading cause of non-pregnancy-related maternal deaths, with some due to injuries from firearms. It was the purpose of this study to characterize the patterns and presentations of firearm-associated injuries in pregnant women using a national emergency department visit database. Data from the Inter-University Consortium for Political and Social Research Firearm Injury Surveillance Study 1993-2020 were utilized. The data include age, sex, race, type of firearm, perpetrator of injury, intent of injury (unintentional, assault, suicide, or law enforcement), anatomic location of the injury, incident locale, disposition from the emergency department (ED), and whether the patient was shot or not with the firearm. Of the 3.36 million ED visits over this time span for firearm injuries, 4410 were pregnant women. The mean age of the pregnant cohort was 23.6 years, with more Hispanic and fewer White women in the pregnant group compared to the non-pregnant cohort. Pregnant women were more likely to experience an injury involving the lower trunk and had a higher percentage of fatalities and hospital admissions compared to the non-pregnant cohort. Fetal demise occurred in at least 70% of cases. Nearly one half of the assaults (44%) occurred on Saturdays and Sundays. As the cause of these injuries is complex, prevention will require input from multiple sources, including health care providers, social agencies, government agencies, elected officials, and law enforcement.

Indexed as

demographicsemergency departmentfetusfirearm injurymortalitypregnancy

Identifiers

PMID37489421
PMCPMC10366773
OpenAlexW4383909658

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.