Evidence map›Paper›PMID 37477803›Full record

SynthesisCurrent heart failure reports2023

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

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

Open access · hybridAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Current heart failure reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.7field-weighted citation impact, top 3% of its field
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

21 citing papers in PubMed, 26 citations in OpenAlex.

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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

10 authors at 5 institutions in 4 countries.

Claartje MeijsJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
M Louis HandokoDepartment of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
Gianluigi SavareseDivision of Cardiology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden.
Robin W M VernooijJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Ilonca VaartjesJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Amitava BanerjeeHealth Data Research UK London, Institute for Health Informatics, University College London, London, UK.
Stefan KoudstaalDepartment of Cardiology, Green Heart Hospital, Gouda, the Netherlands.
Jasper J BrugtsDepartment of Cardiology, Thoraxcenter, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Folkert W AsselbergsHealth Data Research UK London, Institute for Health Informatics, University College London, London, UK.
Alicia UijlJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. a.uijl@amsterdamumc.nl.ORCID 0000-0003-2835-7741
Utrecht University · NLHealth Data Research UK · GBKarolinska Institutet · SEAmsterdam University Medical Centers · NLErasmus MC · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

review purposeThis systematic review aims to summarise clustering studies in heart failure (HF) and guide future clinical trial design and implementation in routine clinical practice.

findings34 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 nine phenotypes: 1) young, low comorbidity burden; 2) metabolic; 3) cardio-renal; 4) atrial fibrillation (AF); 5) elderly female AF; 6) hypertensive-comorbidity; 7) ischaemic-male; 8) valvular disease; and 9) devices. There was room for improvement on important methodological topics for all clustering studies such as external validation and transparency of the modelling process. The large overlap between the phenotypes of the clustering studies shows that clustering is a robust approach for discovering clinically distinct phenotypes. However, future studies should invest in a phenotype model that can be implemented in routine clinical practice and future clinical trial design. HF = heart failure, EF = ejection fraction, HFpEF = heart failure with preserved ejection fraction, HFrEF = heart failure with reduced ejection fraction, CKD = chronic kidney disease, AF = atrial fibrillation, IHD = ischaemic heart disease, CAD = coronary artery disease, ICD = implantable cardioverter-defibrillator, CRT = cardiac resynchronization therapy, NT-proBNP = N-terminal pro b-type natriuretic peptide, BMI = Body Mass Index, COPD = Chronic obstructive pulmonary disease.

Indexed as

Heart FailurePhenotypeStroke VolumeCluster AnalysisHumansClusteringHeart failureMachine learningPhenotypingPrecision medicine

Identifiers

PMID37477803
PMCPMC10589200
OpenAlexW4384924195

What Socratic 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 Socratic graph.