Evidence map›Paper›PMID 42333659›Full record

ArticleJournal of the American Heart Association2026

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

Keiichi Izumi, Ryo Nakamaru, Takashi Kohno, Ayumi Goda, Yasuyuki Shiraishi, Shinsuke Takeuchi, Mitsunobu Kitamura, Yuji Nagatomo, Atsushi Mizuno, Michiru Nomoto and 5 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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5 · Who and what money

Authors and funding

15 authors.

Keiichi IzumiDepartment of Cardiovascular Medicine Kyorin University School of Medicine Tokyo Japan.ORCID 0009-0008-0057-9362
Ryo NakamaruDepartment of Cardiovascular Medicine Kyorin University School of Medicine Tokyo Japan.ORCID 0000-0002-0129-7219
Takashi KohnoDepartment of Cardiovascular Medicine Kyorin University School of Medicine Tokyo Japan.ORCID 0000-0003-2604-1284
Ayumi GodaDepartment of Cardiovascular Medicine Kyorin University School of Medicine Tokyo Japan.ORCID 0000-0002-4388-7639
Yasuyuki ShiraishiDepartment of Cardiology Keio University School of Medicine Tokyo Japan.ORCID 0000-0001-8788-1186
Shinsuke TakeuchiDepartment of Cardiovascular Medicine Kyorin University School of Medicine Tokyo Japan.ORCID 0000-0002-4027-7018
Mitsunobu KitamuraDepartment of Cardiology Sakakibara Heart Institute Tokyo Japan.ORCID 0000-0002-7573-7176
Yuji NagatomoDepartment of Cardiology National Defense Medical College Saitama Japan.ORCID 0000-0002-3430-4614
Atsushi MizunoDepartment of Cardiology St. Lukes International Hospital Tokyo Japan.ORCID 0000-0002-7596-7633
Michiru NomotoDepartment of Cardiology International Medical Center, Saitama Medical University Saitama Japan.
Munehisa SakamotoDepartment of Cardiology, National Hospital Organization Tokyo Medical Center Tokyo Japan.ORCID 0000-0001-5190-856X
Kazutaka MiyamotoDepartment of Cardiology Tokyo Saiseikai Central Hospital Tokyo Japan.ORCID 0009-0005-8220-1205
Kyoko SoejimaDepartment of Cardiovascular Medicine Kyorin University School of Medicine Tokyo Japan.ORCID 0000-0002-0685-4563
Shun KohsakaDepartment of Health Data Science Yokohama City University Graduate School of Data Science Yokohama Japan.ORCID 0000-0003-3779-2972
Tsutomu YoshikawaDepartment of Cardiology Sakakibara Heart Institute Tokyo Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough 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.

methodsA multicenter registry was used to identify patients hospitalized with HF who met at least 1 I NEED HELP criterion. Latent class analysis was performed on 9 variables from the criteria.

resultsA total of 2520 patients (mean age, 74±13 years; 40% women) were included in this study. Latent class analysis identified 3 phenotypes: more de novo HF with the lowest number of applicable criteria (phenotype 1, 31%); younger age with the lowest left ventricular ejection fraction and highest number of applicable criteria (phenotype 2, 19%); and older age with more comorbidities and poorer renal function (phenotype 3, 49%). After multivariable adjustment, phenotypes 2 and 3 were associated with a higher incidence of composite all-cause death or rehospitalization for HF (phenotype 2: hazard ratio [HR], 1.96 [95% CI, 1.58-2.42]; phenotype 3: HR, 1.54 [95% CI, 1.28-1.84]; phenotype 1: reference) during the follow-up period (median, 461 [interquartile range, 130-730] days).

conclusionsThis study describes a novel phenotypical classification based on the I NEED HELP criteria, with significantly different prognoses identified for patients with advanced HF. These classifications may facilitate risk stratification in this population with a complicated clinical profile.

Indexed as

Heart FailureAgedAged, 80 and overComorbidityFemaleHospitalizationHumansLatent Class AnalysisMaleMiddle AgedPatient ReadmissionPhenotypePrognosisRegistriesRisk AssessmentRisk Factorsclassificationheart failureI NEED HELPlatent class analysisprognosis

Identifiers

PMID42333659
PMCPMC13477400

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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.