Evidence map›Paper›PMID 42359428›Full record

ArticleCureus2026

Gaps in Guideline-Directed Medical Therapy for Heart Failure: A Cross-Sectional Study in an Underserved Population.

Ayara O Ehinmisan, Shilpi Jain-Aggarwal, Shweta Karki

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

3 authors.

Ayara O EhinmisanCardiology, University Hospitals Cleveland Medical Center, Cleveland, USA.
Shilpi Jain-AggarwalInternal Medicine, Stamford Hospital, Stamford, USA.
Shweta KarkiResearch, Stamford Hospital, Stamford, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure (HF) remains a major clinical and public health challenge. Guideline-directed medical therapy (GDMT) has been shown to improve outcomes in patients with HF; however, gaps in the prescription and implementation of these therapies persist. These treatment gaps may contribute to suboptimal disease management and adverse clinical outcomes, highlighting the need to better understand patterns of GDMT utilization in diverse patient populations. In this study, we assessed and evaluated the prescribing patterns of GDMTs to an underserved population at an urban federally qualified health center (FQHC).

methodsWe conducted a retrospective chart review of patients diagnosed with HF from May 2022 to June 2024 to assess the prescription of GDMT. Patients were classified based on echocardiographic findings as HF with reduced ejection fraction (HFrEF) (< 50%) and HF with preserved ejection fraction (HFpEF) (≥ 50%). Baseline demographics and prescription of GDMTs were compared between the two HF diagnoses.

resultsFifty patients with HF were identified in the study period, including 41 with HFrEF and nine with HFpEF. There was a significant difference in the mean age between patients diagnosed with HFpEF (68 years) as compared to patients with HFrEF (58 years) (p=0.02). Among patients with HFrEF, 93% (n=38) were prescribed beta-blockers (BB), 83% (n=34) were prescribed angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers/angiotensin receptor-neprilysin inhibitors (ACEi/ARB/ARNi), 29% (n=12) were prescribed mineralocorticoid receptor antagonists (MRA), and 34% (n=14) were prescribed sodium-glucose cotransporter-2 inhibitors (SGLT2). Prescriptions for these medical therapies were similar among patients with HFpEF, except that 0% were prescribed an SGLT2 medication (p=0.05 for comparison with patients with HFrEF).

conclusionsGDMT is under-prescribed in underserved populations, underscoring the need for specific interventions to address financial, systemic, and educational barriers. Interventions such as patient education initiatives, financial counseling support, provider training programs, and policy changes to improve medication affordability and access should be prioritized to help close these treatment gaps.

Indexed as

angiotensin-converting enzyme inhibitors (acei)angiotensin ii receptor blockersbeta blockersguideline directed medical therapyhfpef (heart failure with preserved ejection fraction)hfref (heart failure with reduced ejection fraction)mineralocorticoid receptor antagonistsglt-2 inhibitor

Identifiers

PMID42359428
PMCPMC13292609

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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.