Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Phenotyping of Patients With Clinical Features of Advanced Heart Failure: A Latent Class Analysis of a Multicenter Registry of Patients Hospitalized With Heart Failure.

Journal of the American Heart Association - 7 Jul 2026

Izumi Keiichi, Nakamaru Ryo, Kohno Takashi, Goda Ayumi, Shiraishi Yasuyuki, Takeuchi Shinsuke, Kitamura Mitsunobu, Nagatomo Yuji, Mizuno Atsushi, Nomoto Michiru, Sakamoto Munehisa, Miyamoto Kazutaka, Soejima Kyoko, Kohsaka Shun, Yoshikawa Tsutomu

Abstract excerpt

BACKGROUND: Although the "I NEED HELP" criteria facilitate timely consideration of advanced heart failure (HF) therapies, patient classification based on the variables included in the criteria are scarcely investigated. This study aimed to identify phenotypically distinct subgroups of patients with advanced HF using unsupervised cluster analysis based on the variables included in these criteria. METHODS: A...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Comorbidity
Share to Heart Failure

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Hospitalization

Share to Latent Class Analysis

Share to Registries

Share to Risk Assessment

Share to Stroke Volume

Share to Ventricular Function, Left

Source

Open in PubMed Open full text

Identifiers

PMID: 42333659
DOI: 10.1161/JAHA.126.049046
PMCID: PMC13477400

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Phenotyping of Patients With Clinical Features of Advanced Heart Failure: A Latent Class Analysis of a Multicenter Registry of Patients Hospitalized With Heart Failure.PMID 42333659Read ↗

Identifying novel phenotypes of acute heart failure using cluster analysis of clinical variables.Semantic proximity Read ↗

Identification of distinct phenotypic clusters in heart failure with preserved ejection fractionSemantic proximity Read ↗

Clinical Profiles in Acute Heart FailureSemantic proximity Read ↗

Phenogroups and Their Prognosis of Acute Decompensated Heart Failure with Preserved Ejection Fraction.Semantic proximity Read ↗

Clinical Phenotypes of Heart Failure across the spectrum of Ejection Fraction: A Cluster Analysis.Semantic proximity Read ↗

Clinical implications of chronic heart failure phenotypes defined by cluster analysis.Semantic proximity Read ↗

Prognostic Clinical Phenotypes of Patients with Acute Decompensated Heart Failure.Semantic proximity Read ↗

Clinical phenotypes of heart failure patients with supranormal ejection fraction.Semantic proximity Read ↗

Profiling heart failure with preserved or mildly reduced ejection fraction by cluster analysis.Semantic proximity Read ↗

Phenotyping of acute heart failure with preserved ejection fraction: real-world outcomes in a cohort of older patients.Semantic proximity Read ↗

Phenotype clustering of hospitalized high-risk patients with COVID-19 - a machine learning approach within the multicentre, multinational PCHF-COVICAV registry.Semantic proximity Read ↗

Discovering Distinct Phenotypical Clusters in Heart Failure Across the Ejection Fraction Spectrum: a Systematic Review.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.