Evidence map›Paper›PMID 42382448›Full record

ReviewFrontiers in cardiovascular medicine2026

Finerenone after FINEARTS-HF: evidence boundaries and implementation in heart failure with LVEF ≥40.

Shihang Feng, Hongguang Jin

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2026. 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

2 authors.

Shihang FengCollege of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China.
Hongguang JinThe Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

FINEARTS-HF moved finerenone from cardiorenal biological plausibility to randomized outcome evidence for selected adults with symptomatic heart failure (HF) and left ventricular ejection fraction (LVEF) ≥40%. Finerenone reduced the prespecified composite of cardiovascular death and total worsening HF events, with benefit driven mainly by fewer worsening HF events; cardiovascular death as an individual endpoint was not significantly reduced. This focused narrative Review defines the evidence boundaries after FINEARTS-HF and translates them into clinical implementation for cardiovascular-kidney-metabolic (CKM)-burdened HF with LVEF ≥40%. CKM features are used as a practical framework for risk organization, multimorbidity assessment, competing symptom mechanisms, and monitoring intensity, not as diagnostic criteria, eligibility criteria, or validated predictors of relative response. Safe use requires confirmed symptomatic HF, exclusion of mimickers, confirmation of the local prescribing information, baseline potassium and eGFR assessment, HF-specific dosing, interaction review, laboratory reassessment around 4 weeks after initiation and dose changes, and reassessment during acute illness or unstable renal function. Finerenone should complement SGLT2 inhibitors, decongestion, obesity-directed therapy when indicated, atrial fibrillation care, blood-pressure control, exercise, and nutrition. Future studies should quantify absolute benefit across CKM risk, test UACR, biomarker, and imaging mediation, define combination and sequencing strategies, compare safety with steroidal mineralocorticoid receptor antagonists, and evaluate real-world implementation.

Indexed as

albuminuriacardiovascular-kidney-metabolic syndromefinerenoneheart failureimplementationnonsteroidal mineralocorticoid receptor antagonism

Identifiers

PMID42382448
PMCPMC13314848

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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.