Evidence map›Paper›PMID 41406932›Full record

ArticleJACC. Advances2026

Valvular Heart Disease Associations With Cardiac Biomarkers Using AI-Guided Echocardiography: The RURAL Cohort Study.

Evangelia Alexopoulos, Joanna Walsh, Jesse Y Hsu, Michael J Blaha, Susan Cheng, Melissa A Daubert, Gary Dunn, Peter Durda, Ervin Ray Fox, Yngvil Thomas and 5 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in JACC. Advances, 2026. 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
–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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Evangelia AlexopoulosDepartment of Medicine, Duke University School of Medicine, Duke University, Durham, North Carolina, USA.
Joanna WalshDepartment of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Jesse Y HsuDepartment of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Michael J BlahaDepartment of Medicine, Johns Hopkins, Baltimore, Maryland, USA.
Susan ChengCedars Sinai Medical Center, Los Angeles, California, USA.
Melissa A DaubertDuke Clinical Research Institute and Department of Medicine, Duke University, Durham, North Carolina, USA.
Gary DunnDuke Clinical Research Institute and Department of Medicine, Duke University, Durham, North Carolina, USA.
Peter DurdaDepartment of Pathology & Laboratory Medicine, University of Vermont, Burlington, Vermont, USA.
Ervin Ray FoxDepartment of Medicine, University of Mississippi, Jackson, Mississippi, USA.
Yngvil ThomasGE Healthcare, Chicago, Illinois, USA.
Edwin van den HeuvelDepartment of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, the Netherlands.
Suzanne E JuddDepartment of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Ramachandran S VasanUniversity of Texas School of Public Health and Health Sciences Center, San Antonio, Texas, USA.
Pamela S DouglasDuke Clinical Research Institute and Department of Medicine, Duke University, Durham, North Carolina, USA.
Gerald S BloomfieldDuke Clinical Research Institute and Department of Medicine, Duke University, Durham, North Carolina, USA; Duke Global Health Institute, Duke University, Durham, North Carolina, USA. Electronic address: gerald.bloomfield@duke.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew studies have evaluated the prevalence or severity of mitral valve prolapse (MVP) and other valvular heart disease (VHD) in the rural U.S. South, where strategies for early detection are crucial for risk stratification and prevention.

objectivesWe assessed the prevalence of MVP and other VHD in a rural U.S. South cohort and examined associations with cardiovascular disease (CVD) risk. We also evaluated associations between MVP severity, high-sensitivity cardiac troponin T, and N-terminal pro-B-type natriuretic peptide.

methodsWe conducted a cross-sectional analysis from the Risk Underlying Rural Areas Longitudinal study. Logistic regression assessed associations between participant characteristics and MVP, other VHD, or either. Weighted models assessed odds for MVP and other VHD by 10-year CVD risk categories using the Predicting Risk of CVD Events (PREVENT) score. Among a subset, we evaluated associations between MVP severity and cardiac biomarkers.

resultsAmong 2,621 participants (68.7% women), MVP and other VHD were present in 1.9% and 11.2%, respectively. Compared to the low PREVENT risk group, odds of MVP were lower and odds of VHD were higher among borderline and intermediate/high groups. High-sensitivity cardiac troponin T was lower in MVP vs non-MVP (0.64; 95% CI: 0.58-0.71), without difference by severity of MVP. N-terminal pro-B-type natriuretic peptide was higher in participants with severe MVP than non-MVP (2.03; 95% CI: 1.49-2.78).

conclusionsMVP prevalence aligned with population-based epidemiologic studies. PREVENT risk category may identify individuals at higher risk for MVP and for other VHD. Future studies are needed to evaluate relationships between MVP/VHD status and clinical events.

Indexed as

biomarkersmitral valve prolapserural countiesvalvular heart disease

Identifiers

PMID41406932
PMCPMC12869879

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.