Evidence map›Paper›PMID 40601199›Full record

ArticleJournal of general internal medicine2025

Incident Atherosclerotic Cardiovascular Disease Among Veterans by Gender Identity: A Cohort Study.

Carl G Streed, Meredith S Duncan, Kory R Heier, T Elizabeth Workman, Lauren B Beach, Guneet K Jasuja, Hill L Wolfe, Landon D Hughes, John R O'Leary, Melissa Skanderson and 1 more

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Cardiometabolic diseases in transgender populations.Cardiovascular diabetology. Endocrinology reports · 2026
    Review
  2. 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

11 authors.

Carl G StreedDepartment of Medicine, Section of General Internal Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA. Carl.Streed@bmc.org.ORCID 0000-0003-3075-253X
Meredith S DuncanDepartment of Biostatistics, University of Kentucky, Lexington, KY, USA.
Kory R HeierDepartment of Biostatistics, University of Kentucky, Lexington, KY, USA.
T Elizabeth WorkmanBiomedical Informatics Center, George Washington University, Washington, DC, USA.
Lauren B BeachDepartment of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Guneet K JasujaDepartment of Medicine, Section of General Internal Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
Hill L WolfeDepartment of Biomedical Informatics & Data Science, Yale School of Medicine, New Haven, CT, USA.
Landon D HughesDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
John R O'LearyDepartment of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
Melissa SkandersonDepartment of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
Joseph L GouletDepartment of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA.

Funding

Institutional Career Development CoreKL2TR001996 · NCATS · UNIVERSITY OF KENTUCKY · PI BUSH, MATTHEW LEE, KELLY, THOMAS H. · 2016 to 2025
$7.1M
Building methods to assess and address cardiovascular health in transgender adultsK01HL151902 · NHLBI · BOSTON MEDICAL CENTER · PI Carl G Streed · 2021 to 2026
$863k
NCATS NIH HHS KL2 TR001996NHLBI NIH HHS K01 HL151902
6 · The paper itself

Abstract

backgroundTransgender and gender diverse (trans) populations are at elevated risk for atherosclerotic cardiovascular disease (ASCVD).

objectiveMeasure the association of gender identity and gender-affirming hormone therapy (GAHT) with ASCVD outcomes.

designCohort study.

participantsOver 1 million veterans receiving care in the Veterans Health Administration. MAIN MEASURES: Gender identity was identified via a validated natural language processing (NLP) algorithm. Incident ASCVD (acute myocardial infarction, ischemic stroke, or revascularization after the baseline date) was identified via International Classification of Diseases diagnosis codes among veterans without prevalent ASCVD. We calculated sample statistics stratified by gender identity and used Cox proportional hazard regression to assess associations of gender identity and GAHT with incident ASCVD. KEY

resultsAmong 1,105,082 veterans, 42,149 were classified as trans (8013 transfeminine, 7127 transmasculine, and 27,009 uncategorized trans) while 918,843 were cisgender men and 144,090 were cisgender women. During a median follow-up of 9.39 years, 92,910 veterans had incident ASCVD (2806 among trans veterans). Adjusting for age, race, Hispanic ethnicity, and sexual orientation, trans veterans had 1.52 [1.45, 1.59] and 0.92 [0.89, 0.96] times the hazard of ASCVD compared to cisgender women and cisgender men, respectively. Compared to trans veterans not receiving GAHT, GAHT among trans veterans assigned female at birth was significantly associated a reduced hazard of ASCVD (0.89 [0.80, 0.98]); GAHT was not associated with ASCVD among trans veterans assigned male at birth (0.99 [0.89, 1.09]). LIMITATIONS: With NLP, there is potential for selection bias as clinicians may preferentially document the gender identity for trans more than cisgender veterans.

conclusionsThis is one of the first studies to examine the association of both gender identity and GAHT with incident ASCVD in veterans. Future research must comprehensively evaluate ASCVD outcomes and the effects of gender-affirming care (including hormone therapy) in trans populations.

Indexed as

AtherosclerosisGender IdentityTransgender PersonsVeteransAdultAgedCohort StudiesFemaleHumansIncidenceMaleMiddle AgedUnited States

Identifiers

PMID40601199
PMCPMC12508330

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Registered trials

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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.