Evidence map›Paper›PMID 41058133›Full record

ArticleNuclear medicine communications2025

Clinical phenotypes among patients that underwent cardiac resynchronization therapy using unsupervised learning integrating gated SPECT.

Giovane Leal de Azevedo Junior, Noah Painter, Zhuo He, Kristoffer Larsen, Qiuying Sha, Xinwei Zhang, Jiangang Zou, Guang-Uei Hung, Amalia Peix, Claudio Tinoco Mesquita and 1 more

Abstract read
In one paragraph

Article in Nuclear medicine communications, 2025. 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

11 authors.

Giovane Leal de Azevedo JuniorHospital Universitário Antônio Pedro - Ebserh, Universidade Federal Fluminense, Niterói, Brazil.ORCID 0009-0001-1083-2332
Noah PainterDepartments of Mathematical Sciences.
Zhuo HeApplied Computing, Michigan Technological University, Houghton, Michigan, USA.ORCID 0000-0002-3805-4579
Kristoffer LarsenDepartments of Mathematical Sciences.
Qiuying ShaDepartments of Mathematical Sciences.ORCID 0000-0002-9342-3269
Xinwei ZhangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jiangang ZouDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0001-5891-6589
Guang-Uei HungDepartment of Nuclear Medicine, Chang Bing Show Chwan Memorial Hospital, Changhua, Taiwan.
Amalia PeixNuclear Medicine Department, Institute of Cardiology, La Habana, Cuba.ORCID 0000-0001-5805-1810
Claudio Tinoco MesquitaHospital Universitário Antônio Pedro - Ebserh, Universidade Federal Fluminense, Niterói, Brazil.ORCID 0000-0002-1466-9413
Weihua ZhouApplied Computing, Michigan Technological University, Houghton, Michigan, USA.ORCID 0000-0002-6039-959

Funding

Integrative analysis of electrical and mechanical dyssynchrony to improve cardiac resynchronization therapyR15HL173852 · NHLBI · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI SHA, QIUYING · 2024 to 2024
$429k
Multi-modality Image Fusion to Improve Coronary Revascularization in Patients with Stable Coronary Artery DiseaseR15HL172198 · NHLBI · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI ZHOU, WEIHUA · 2024 to 2024
$427k
Clinical Competence Improvement Project of Jiangsu Province Hospital JSPH-MA-2020-3National Science and Technology Major Project of China 2023ZD0504200NHLBI NIH HHS R15 HL172198NHLBI NIH HHS R15 HL173852Project on New Technology of Jiangsu Province JX233C202103
6 · The paper itself

Abstract

backgroundCardiac resynchronization therapy (CRT) is an effective treatment for heart failure when left ventricular mechanical dyssynchrony (LVdys) is present, yet approximately 30-40% of patients do not respond to therapy. The purpose of this study is to use unsupervised learning to identify phenotypes of patients with a better response rate.

methodsUnsupervised learning integrating gated single-photon emission computed tomography (SPECT) was used to identify clinical phenotypes among patients undergoing CRT. We utilized hierarchical clustering analysis to group 217 patients based on 49 pretreatment variables, including demographic, clinical, and phase analysis of gated SPECT data. Fibrosis was measured by the percentage of pixels with less than 50% of maximum relative counts. LVdys was evaluated by phase SD >43° and phase bandwidth >135°.

resultsWe identified three phenotypes of patients: two with similar response rates (86.2 and 87.0%) but with different characteristics, one presenting borderline LVdys, low fibrosis and nondilated heart and the other high LVdys, moderate fibrosis and a dilated heart; the third phenotype represents patients with moderate LVdys, substantial amounts of cardiac fibrosis and a dilated heart that do not have a good response to CRT (55.9%).

conclusionOur results suggest that evaluating cardiac dyssynchrony, fibrosis, and remodeling through phase analysis of gated SPECT is relevant in characterizing the phenotype of good responders. Patients with substantial amounts of cardiac fibrosis have less benefit from CRT. This work suggests that CRT recommendations based on customized selection criteria associated with gated SPECT can lead to higher response rates.

Indexed as

Cardiac-Gated Single-Photon Emission Computer-Assisted TomographyCardiac Resynchronization TherapyUnsupervised Machine LearningAgedFemaleHumansMaleMiddle AgedPhenotypecardiac resynchronization therapynuclear cardiologySPECTunsupervised learning

Identifiers

PMID41058133
PMCPMC12888763

What OpenQuestion holds

Textmetadata
LicenceTDM
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.