Evidence map›Paper›PMID 41848050›Full record

ArticleJournal of the American Heart Association2026

Prevalence and Incidence of Heart Failure Phenotypes Among Transgender and Gender-Diverse Adults in the United States.

Ian K Everitt, Emily K Quinn, Meredith S Duncan, Chris Grasso, Sari L Reisner, Guneet K Jasuja, Tonia Poteat, Ayelet Shapira-Daniels, Howard Cabral, Vin Tangpricha and 4 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

14 authors.

Ian K Everitt *Division of Cardiology Johns Hopkins University School of Medicine Baltimore MD USA.ORCID 0000-0002-9941-438X
Emily K Quinn *Biostatistics and Epidemiology Data Analytics Center Boston University School of Public Health Boston MA USA.ORCID 0000-0002-9574-2909
Meredith S DuncanDepartment of Biostatistics University of Kentucky Lexington KY USA.ORCID 0000-0001-6922-8503
Chris GrassoFASTx Partners Boston MA USA.ORCID 0000-0003-0782-5016
Sari L ReisnerDepartment of Epidemiology University of Michigan School of Public Health Ann Arbor MI USA.ORCID 0000-0001-7868-4746
Guneet K JasujaSection of General Internal Medicine Boston University Chobanian and Avedisian School of Medicine Boston MA USA.
Tonia PoteatDuke University School of Nursing Durham NC USA.ORCID 0000-0001-6541-3787
Ayelet Shapira-DanielsDepartment of Medicine Boston Medical Center Boston MA USA.ORCID 0000-0002-4920-2397
Howard CabralDepartment of Biostatistics School of Public Health, Boston University Boston MA USA.ORCID 0000-0002-1185-8331
Vin TangprichaDivision of Endocrinology, Metabolism and Lipids, Department of Medicine School of Medicine, Emory University Atlanta GA USA.ORCID 0000-0002-4021-5853
Michael K Paasche-OrlowDepartment of Medicine Tufts Medical Center Boston MA USA.ORCID 0000-0002-9276-7190
Emelia J BenjaminSection of Cardiovascular Medicine, Department of Medicine Boston University Chobanian and Avedisian School of Medicine and Boston Medical Center Boston MA USA.ORCID 0000-0003-4076-2336
Monica MukherjeeDivision of Cardiology Johns Hopkins University School of Medicine Baltimore MD USA.ORCID 0000-0001-6088-0773
Carl G StreedBoston University Chobanian and Avedisian School of Medicine Boston MA USA.ORCID 0000-0003-3075-253X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevalent and incident heart failure (HF) and its comorbidities have not been characterized in transgender and gender-diverse (TGD) populations. This study determines the prevalence and incidence of HF phenotypes by gender identity.

methodsA retrospective cohort analysis was performed using deidentified administrative claims from the Optum Labs Data Warehouse (2006-2022). TGD adults and a sample of demographically similar cisgender comparators were identified using a validated algorithm, and gender identity was categorized as cisgender man, cisgender woman, transmasculine, transfeminine, or unclassified TGD. Prevalent and incident HF, including systolic, diastolic, and unclassified phenotypes, were assessed using diagnosis codes. Multivariable logistic and Cox regression models adjusted for age and comorbidities evaluated associations between gender identity and HF.

resultsIn this cohort of 57 471 TGD individuals and 298 213 demographically similar cisgender comparators, 17 898 TGD people (31.1%) were transmasculine, 9652 (16.8%) were transfeminine, and 29 921 (52.1%) had unclassified TGD identity. In adjusted models, transmasculine people experienced less prevalent systolic HF than cisgender men (odds ratio, 0.37 [98.75% CI, 0.17-0.83]) and women (odds ratio, 0.42 [98.75% CI, 0.19-0.92]). Transmasculine people experienced less incident diastolic HF relative to cisgender men (hazard ratio [HR], 0.65 [98.75% CI, 0.51-0.82]) and women (HR, 0.66 [98.75% CI, 0.52-0.83]). Transfeminine people experienced more incident diastolic HF than cisgender men (HR, 1.36 [98.75% CI, 1.05-1.77]) and women (HR, 1.38 [98.75% CI, 1.07-1.79]).

conclusionsPrevalent systolic HF and incident diastolic HF differed by gender identity after adjustment for age and clinical comorbidities. Further research is needed to identify underrecognized sex- and gender-based HF risk modifiers.

Indexed as

Heart FailureTransgender PersonsAdultAgedFemaleGender-Nonconforming PersonsHumansIncidenceMaleMiddle AgedPhenotypePrevalenceRetrospective StudiesRisk FactorsUnited Statescardiovascular healthheart failuretransgender

Identifiers

PMID41848050
PMCPMC13279251

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.