Evidence map›Paper›PMID 39895530›Full record

Observational studyJournal of the American Heart Association2025

Phenotypic Trajectories From Acute to Stable Phase in Heart Failure With Preserved Ejection Fraction: Insights From the PURSUIT-HFpEF Study.

Yuki Matsuoka, Yohei Sotomi, Daisaku Nakatani, Katsuki Okada, Akihiro Sunaga, Hirota Kida, Taiki Sato, Daisuke Sakamoto, Tetsuhisa Kitamura, Sho Komukai and 11 more

Abstract readObservational StudyMulticenter Study
In one paragraph

Observational study in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. 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

21 authors.

Yuki MatsuokaDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.
Yohei SotomiDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0002-7564-2978
Daisaku NakataniDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0002-1534-2033
Katsuki OkadaDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0002-1725-781X
Akihiro SunagaDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0003-2590-6696
Hirota KidaDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.
Taiki SatoDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.
Daisuke SakamotoDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.
Tetsuhisa KitamuraDepartment of Social and Environmental Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0003-0107-0580
Sho KomukaiDivision of Biomedical Statistics, Department of Integrated Medicine, Graduate School of Medicine Osaka University Osaka Japan.ORCID 0000-0002-4329-2520
Masahiro SeoDivision of Cardiology Osaka General Medical Center Osaka Japan.ORCID 0000-0001-6517-486X
Masamichi YanoDivision of Cardiology Osaka Rosai Hospital Osaka Japan.
Takaharu HayashiCardiovascular Division Osaka Police Hospital Osaka Japan.ORCID 0000-0003-1637-4536
Akito NakagawaDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0001-8276-1505
Yusuke NakagawaDivision of Cardiology Kawanishi City Medical Center Amagasaki Hyogo Japan.ORCID 0000-0001-5523-0856
Shunsuke TamakiDepartment of Cardiology Rinku General Medical Center Osaka Japan.ORCID 0000-0001-5642-3836
Yoshio YasumuraDivision of Cardiology Amagasaki Chuo Hospital Amagasaki Hyogo Japan.
Takahisa YamadaDivision of Cardiology Osaka General Medical Center Osaka Japan.ORCID 0000-0002-6435-7506
Shungo HikosoDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0003-2284-1970
Yasushi SakataDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka Japan.ORCID 0000-0002-5618-4721
OCVC‐Heart Failure Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUsing machine learning for the phenotyping of patients with heart failure with preserved ejection fraction (HFpEF) has emerged as a novel approach to understanding the pathophysiology and stratifying the patients. Our objective is to perform phenotyping of patients with HFpEF in stable phase and to investigate the phenotypic trajectory from acute worsening phase to stable phase.

methodsThe present study is a post hoc analysis of the PURSUIT-HFpEF (Prospective Multicenter Observational Study of Patients with Heart Failure with Preserved Ejection Fraction) study. We applied the latent class analysis to the discharge data of patients hospitalized for acute decompensated heart failure.

resultsWe finally included patient data of 1100 cases and 63 features in the latent class analysis. All patients were subclassified into 5 phenogroups as follows: Phenotype 1, characterized by better renal function and lower NT-proBNP (N-terminal pro-B-type natriuretic peptide) level [N=325 (29.5%)]; Phenotype 2, higher blood pressure, sinus rhythm, and poor renal function. [N=242 (22.0%)]; Phenotype 3, higher prevalence of atrial fibrillation, higher tricuspid pressure gradient, and lower tricuspid annular plane systolic excursion [N=214 (19.5%)]; Phenotype 4, higher C-reactive protein level and higher tricuspid pressure gradient [N=245 (22.3%)]; and Phenotype 5, poor nutritional status, poor renal function, and higher NT-proBNP level [N=74 (6.7%)]. A particular phenotype observed at the time of discharge was correlated with a distinct phenotype of acute worsening.

conclusionsWe identified 5 distinct stable phase phenotypes of the patients with HFpEF from the data at discharge. A specific phenotype at discharge was associated with a particular phenotype of acute worsening. This grouping can be a basis for future precision medicine of patients with HFpEF. REGISTRATION: URL: https://www.umin.ac.jp/ctr/; Unique identifier: UMIN000021831.

Indexed as

Heart FailureStroke VolumeVentricular Function, LeftAgedAged, 80 and overDisease ProgressionFemaleHumansMaleMiddle AgedNatriuretic Peptide, BrainPeptide FragmentsPhenotypeProspective StudiesNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)HFpEFlatent class analysismachine learningphenotyping

Identifiers

PMID39895530
PMCPMC12074776

What Socratic holds

Textmetadata
LicenceCC BY
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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.