Evidence map›Paper›PMID 41028654›Full record

ReviewHeart failure reviews2025

Phenotype-guided approach for device-based therapies in heart failure.

Phuuwadith Wattanachayakul, Veraprapas Kittipibul, William T Abraham, Rebecca T Hahn, Sean P Pinney, Akshay S Desai, Daniel Burkhoff, Marat Fudim

Abstract readReview
PubMed Publisher
In one paragraph

Review in Heart failure reviews, 2025. 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. Machine learning-derived clinical phenotypes of ascites in cirrhosis: A multi-center latent class analysis with external validation.Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society · 2026
    Article
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

8 authors.

Phuuwadith WattanachayakulDepartment of Medicine, Jefferson Einstein Hospital, Philadelphia, PA, USA.
Veraprapas KittipibulDepartment of Internal Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA.
William T AbrahamDivision of Cardiovascular Medicineand the Davis Heart and Lung Research Institute, The Ohio State University College of Medicine, Columbus, OH, USA.
Rebecca T HahnColumbia University Irving Medical Center, New York, NY, USA.
Sean P PinneyIcahn School of Medicine at Mount Sinai, Mount Sinai Fuster Heart Hospital, New York, NY, USA.
Akshay S DesaiCardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Daniel BurkhoffCardiovascular Research Foundation, New York, NY, USA.
Marat FudimDepartment of Internal Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA. marat.fudim@duke.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Device-based therapies have become integral in the management of heart failure (HF). By targeting structural or neurohormonal pathways, these therapies provide additional benefits beyond those provided by pharmacologic therapies or correct structural abnormalities that may not be amenable to drug therapy. However, a comprehensive framework for device selection tailored to individual clinical profiles and comorbidities has not yet been proposed, and many potentially effective approaches are underutilized among eligible patients in clinical practice. The availability of such a framework could help maximize the benefits of available therapies for the broad population of patients with HF. In this review, we explore the current role of device-based HF therapies in clinical practice based on available evidence from clinical trials and propose a phenotype-driven framework to guide device selection in HF patients with reduced and preserved ejection fraction. We also outline future directions, emphasizing opportunities to improve HF care.

Indexed as

Cardiac Resynchronization TherapyDefibrillators, ImplantableHeart-Assist DevicesHeart FailureHumansPhenotypeStroke VolumeDevice therapyHeart failureHeart failure with preserved ejection fractionHeart failure with reduced ejection fraction

Identifiers

PMID41028654

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.