Evidence map›Paper›PMID 42140811›Full record

ArticleHeart, lung & circulation2026

Characterising Multimorbidity in Adults With Heart Failure: A Latent Class Analysis.

Shirin O Hiatt, Paula M Meek, Bob G Wong, Christopher S Lee, Quin E Denfeld

Abstract read
In one paragraph

Article in Heart, lung & circulation, 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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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Shirin O HiattOregon Health & Science University School of Nursing, Portland, OR, USA; University of Utah, College of Nursing, Salt Lake City, UT, USA. Electronic address: hiatts@ohsu.edu.
Paula M MeekUniversity of Utah, College of Nursing, Salt Lake City, UT, USA.
Bob G WongUniversity of Utah, College of Nursing, Salt Lake City, UT, USA.
Christopher S LeeBoston College William F. Connell School of Nursing, Chestnut Hill, MA, USA; Division of Scientific Research and Innovation in Emergency Medical Service, Department of Emergency Medical Service, Faculty of Nursing and Midwifery, Wroclaw Medical University, Poland.
Quin E DenfeldOregon Health & Science University School of Nursing, Portland, OR, USA; Oregon Health & Science University Knight Cardiovascular Institute Portland, OR, USA.

Funding

Oregon Clinical and Translational Research Institute - The National COVID Cohort Collaborative (N3C)UL1TR002369 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI Cynthia D Morris, Christopher G. Slatore · 2017 to 2026
$78.4M
Scholars in Women's Health Research Across the LifespanK12HD043488 · NICHD · OREGON HEALTH & SCIENCE UNIVERSITY · PI MYATT, LESLIE · 2002 to 2023
$10.4M
Profiling Biobehavioral Responses to Mechanical Support in Advanced Heart FailureR01NR013492 · NINR · OREGON HEALTH & SCIENCE UNIVERSITY · PI LEE, CHRISTOPHER SEAN · 2012 to 2015
$1.4M
Symptom Biology and Accelerated Aging in Heart FailureF31NR015936 · NINR · OREGON HEALTH & SCIENCE UNIVERSITY · PI DENFELD, QUIN ELEANOR · 2015 to 2015
$42k
NCATS NIH HHS UL1 TR002369NICHD NIH HHS K12 HD043488NINR NIH HHS F31 NR015936NINR NIH HHS R01 NR013492
6 · The paper itself

Abstract

introduction/purposeMultimorbidity (MM) is highly prevalent in patients with heart failure (HF) and associated with worse outcomes; however, our understanding of the heterogeneity of MM in HF is limited. The purpose of this study was to identify and characterise MM classes among adults with HF. METHODS AND

resultsWe conducted a retrospective modified cross-sectional analysis of the combined baseline data repository of adults with New York Heart Association Class I-IV HF enrolled at a single healthcare centre. Comorbidities were assessed with the Charlson Comorbidity Index (CCI), and latent class mixture modeling was used to identify MM classes. Descriptive and comparative statistics were used to characterise classes. The sample (n=523) was 73% male, with an average age of 58.3±14.0 years. Nearly 92% of the sample had at least one additional comorbidity with hypertension (59%), atrial fibrillation (48%), sleep apnoea/disordered breathing (41%), diabetes (40%), and myocardial infarction (36%) as the most prevalent comorbidities. We identified four distinct MM classes of comorbidity dominance: neurovascular-renal (4.5%; oldest, living alone, highest CCI), obesity-metabolic (31.7%; second-oldest, married/partnered, most financial instability), atrial fibrillation (31.9%; lowest CCI), and early comorbidity (31.9%; youngest, second-most financial instability) in patients with HF, each with differences in characteristics.

conclusionsWe found multiple classes of MM with varying characteristics that may have implications for HF management. Coupled with geriatric cardiology principles related to MM, these findings highlight the need to explore the occurrence of MM, including its effects on patient outcomes, and to provide appropriate person-centred care.

Indexed as

Heart FailureLatent Class AnalysisAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedMultimorbidityPrevalenceRetrospective StudiesGeriatric syndromeHeart failureMultimorbidity

Identifiers

PMID42140811
PMCPMC13214150

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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.