Evidence map›Paper›PMID 40710766›Full record

ReviewJournal of cardiovascular development and disease2025

Prediction of Right Heart Failure in LVAD Candidates: Current Approaches and Future Directions.

Frederick Vogel, Zachary W Sollie, Arman Kilic, Ethan Kung

Abstract readReview
In one paragraph

Review in Journal of cardiovascular development and disease, 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. Review
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

4 authors.

Frederick VogelDepartment of Bioengineering, College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, SC 29634, USA.
Zachary W SollieDepartment of Surgery, Division of Cardiothoracic Surgery, Medical University of South Caroline, Charleston, SC 29425, USA.
Arman KilicDepartment of Surgery, Division of Cardiothoracic Surgery, Medical University of South Caroline, Charleston, SC 29425, USA.
Ethan KungDepartment of Bioengineering, College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0002-2532-2458

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Right heart failure is a condition where the right ventricle fails to pump blood into the pulmonary artery, and, in turn, the lungs. This condition frequently presents after the implantation of a left ventricular assist device (LVAD). Ventricular assist candidates who have LVADs implanted possess various pathophysiological and cardiovascular features that contribute to the later development of RHF. With LVADs serving as bridge-to-transplantation, bridge-to-candidacy, and destination therapies, it is imperative that the pre-operative indicators of RHF are identified and assessed. Multiple predictive models and parameters have been developed to quantify the risk of post-LVAD right heart failure. Clinical, laboratory, hemodynamic, and echocardiographic parameters have all been used to develop these predictive approaches. RHF remains a major cause of morbidity and mortality after LVAD implantation. Predicting RHF helps clinicians assess treatment options, including biventricular support or avoiding high-risk surgery. In our review, we noted the varying definitions for RHF in recent models, which affected respective predictive accuracies. The pulmonary arterial pulsatile index (PAPi) and right ventricular longitudinal strain parameters were noted for their potential to enhance current models incrementally. Meanwhile, mechanistic and machine learning approaches present a more fundamental shift in the approach to making progress in this field.

Indexed as

ALMA scoreCRITT scoreEUROMACS scoreMCRN scoremechanical circulatory supportMichigan scorephysiology simulation coupled experimentpulmonary artery pulsatile indexright heart failureright ventricular longitudinal strainVAD

Identifiers

PMID40710766
PMCPMC12295032

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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.