Evidence map›Paper›PMID 40014229›Full record

ReviewCurrent cardiology reports2025

Sociodemographic Disparities in Obtaining Cardiac MRI: Black, White, and Shades of Gray.

Ololade Akingbade, Elizabeth Cabrera, Varun Subashchandran, Ryan Yang, Neal Shah, Hena Patel, Jeremy A Slivnick

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 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

7 authors.

Ololade AkingbadeUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA.
Elizabeth CabreraUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA.
Varun SubashchandranUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA.
Ryan YangUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA.
Neal ShahUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA.
Hena PatelUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA.
Jeremy A SlivnickUniversity of Chicago Medicine, 5758 S. Maryland Ave M.C. 9067, Chicago, IL, 60637, USA. Jslivnick@uchicagomedicine.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewDespite growing recommendations for CMR utilization in heart disease evaluation, access remains limited by geography and socioeconomic status. In this review we discuss the role of CMR in addressing health disparities, review barriers to CMR access, and finally propose solutions to increasing CMR testing globally and in the U.S. RECENT

findingsCMR testing is higher prevalence in academic and urban centers in the Northeast and Midwest and remains sparser in Southern and rural areas which face a high burden of cardiovascular mortality. Globally, CMR is also limited in low- and middle-income countries. Barriers to CMR access include bias in physician referrals based on race, patient income, insurance status, language barriers, health literacy, and disparities in the multimodal cardiovascular imaging workforce. A multimodal approach involving policy makers, hospital systems, cardiologists, and health care personnel is essential to improving national and global barriers to accessing CMR.

Indexed as

Healthcare DisparitiesHealth Services AccessibilityHeart DiseasesMagnetic Resonance ImagingHumansRacial GroupsSocioeconomic FactorsUnited StatesCardiac imagingCardiac magnetic resonanceDisparities

Identifiers

What OpenQuestion holds

Textmetadata
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.