Evidence map›Paper›PMID 40428103›Full record

ArticleBioengineering (Basel, Switzerland)2025

Machine Learning Prediction of Left Ventricular Assist Device Thrombosis from Acoustic Harmonic Power.

Kent D Carlson, Dan Dragomir-Daescu, Barry A Boilson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioengineering (Basel, Switzerland), 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

3 authors.

Kent D CarlsonDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA.
Dan Dragomir-DaescuDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA.
Barry A BoilsonDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0003-2043-4204

Funding

Mayo Clinic Internal funding
6 · The paper itself

Abstract

Left ventricular assist device (LVAD) thrombosis typically presents late and may have devastating consequences for patients. While LVAD pump thrombosis is uncommon with current pump designs, many patients worldwide remain supported with previous generations of LVADs, including the HeartWare device (HVAD). Researchers have focused on investigating the acoustic signatures of LVADs to enable earlier detection and treatment of this condition. This study explored the use of machine learning algorithms to predict thrombosis from harmonic power values determined from the acoustic signatures of a cohort of HVAD patients (

Indexed as

harmonic frequenciesharmonic powerHeartWare ventricular assist device (HVAD)K-nearest neighborsleft ventricular assist device (LVAD)machine learningprincipal component analysisspectral analysisthrombosis

Identifiers

PMID40428103
PMCPMC12109467

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.