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

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

Current heart failure reports - 1 Oct 2023

Meijs Claartje, Handoko M Louis, Savarese Gianluigi, Vernooij Robin W M, Vaartjes Ilonca, Banerjee Amitava, Koudstaal Stefan, Brugts Jasper J, Asselbergs Folkert W, Uijl Alicia

Abstract excerpt

REVIEW PURPOSE: This systematic review aims to summarise clustering studies in heart failure (HF) and guide future clinical trial design and implementation in routine clinical practice. FINDINGS: 34 studies were identified (n = 19 in HF with preserved ejection fraction (HFpEF)). There was significant heterogeneity invariables and techniques used. However, 149/165 described clusters could be assigned to one of...

Topics

Join the communities discussing this publication.

Cluster Analysis
Heart Failure
Phenotype
Stroke Volume

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Open in PubMed Open full text

Identifiers

PMID: 37477803
DOI: 10.1007/s11897-023-00615-z
PMCID: PMC10589200

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

Community interpretation

Discuss the evidence

Ask a question, add context or challenge an interpretation. Community activity is separate from scientific evidence strength.

0

discussions

0

replies

Citations encouraged

Claims remain attributable.

No discussion yet

Be the first to add a careful, cited interpretation.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Discovering Distinct Phenotypical Clusters in Heart Failure Across the Ejection Fraction Spectrum: a Systematic Review.PMID 37477803Read ↗

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

Heart failure with preserved ejection fraction: A clustering approach to a heterogenous syndrome.Semantic proximity Read ↗

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

Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning.Semantic proximity Read ↗

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

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

Biomarker Phenotypes in Heart Failure with Preserved Ejection Fraction Using Hierarchical Clustering: A Pilot Study.Semantic proximity Read ↗

Medications for specific phenotypes of heart failure with preserved ejection fraction classified by a machine learning-based clustering model.Semantic proximity Read ↗

The HeartMagic prospective observational study protocol – characterizing subtypes of heart failure with preserved ejection fractionSemantic proximity Read ↗

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

Phenomapping Heart Failure with Preserved Ejection Fraction Using Machine Learning Cluster Analysis: Prognostic and Therapeutic Implications.Semantic proximity Read ↗

Machine Learning Methods Improve Prognostication, Identify Clinically Distinct Phenotypes, and Detect Heterogeneity in Response to Therapy in a Large Cohort of Heart Failure Patients.Semantic proximity Read ↗

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