Evidence map›Paper›PMID 41553073›Full record

Observational studyJournal of the American Heart Association2026

Low Serum Lysophospholipids Predict Increased In-Hospital Mortality in Patients With Acute Heart Failure.

Iva Klobučar, Gudrun Pregartner, Gerald Rechberger, Thomas O Eichmann, Ines Potočnjak, Matias Trbušić, Hansjörg Habisch, Bastian Pfeifer, Tobias Madl, Andrea Berghold and 2 more

Abstract readObservational Study
In one paragraph

Observational study 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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0cells of the map it votes in
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

12 authors.

Iva Klobučar *Department of Cardiology Sisters of Charity University Hospital Center Zagreb Croatia.ORCID 0000-0002-0640-7149
Gudrun Pregartner *Institute for Medical Informatics, Statistics und Documentation Medical University of Graz Graz Austria.ORCID 0000-0002-9899-0502
Gerald RechbergerInstitute of Molecular Biosciences University of Graz Graz Austria.ORCID 0000-0002-0071-317X
Thomas O EichmannCore Facility Mass Spectrometry, Center for Medical Research Medical University of Graz Graz Austria.ORCID 0000-0002-8521-2795
Ines PotočnjakSisters of Charity University Hospital Center Zagreb Croatia.ORCID 0000-0001-9351-9669
Matias TrbušićSisters of Charity University Hospital Center Zagreb Croatia.ORCID 0000-0001-9428-454X
Hansjörg HabischMedicinal Chemistry, Otto Loewi Research Center Medical University of Graz Graz Austria.ORCID 0000-0001-5537-506X
Bastian PfeiferInstitute for Medical Informatics, Statistics und Documentation Medical University of Graz Graz Austria.ORCID 0000-0001-7035-9535
Tobias MadlBioTechMed-Graz Graz Austria.ORCID 0000-0002-9725-5231
Andrea BergholdInstitute for Medical Informatics, Statistics und Documentation Medical University of Graz Graz Austria.ORCID 0000-0001-5187-9105
Saša FrankBioTechMed-Graz Graz Austria.ORCID 0000-0003-4826-7698
Vesna DegoricijaSisters of Charity University Hospital Center Zagreb Croatia.ORCID 0000-0001-6226-4018

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNew biomarkers are needed to improve risk prediction in patients with acute heart failure. We aimed to identify serum lipids with prognostic value and clinical utility in patients hospitalized due to acute heart failure.

methodsTargeted mass spectrometry-based lipidomics was performed on serum samples from 315 (discovery) and 139 (validation) patients prospectively enrolled in 2 observational acute heart failure studies. Prognostic lipids were identified by consolidating orthogonal partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest (Boruta) results into a single ranking using TopKSignal.

resultsIn the discovery cohort, lysophosphatidylethanolamine 20:4, lysophosphatidylcholine 20:4, lysophosphatidylcholine 14:0, and lysophosphatidylethanolamine 18:1 were most strongly associated with in-hospital mortality. Serum concentrations were significantly lower in nonsurvivors, and these inverse associations remained significant after adjustment in both cohorts, except for lysophosphatidylethanolamine 18:1 after adjustment for OPTIMIZE-HF (Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure) in the validation cohort. These lipids demonstrated moderate discriminative performance (area under the curve, 0.72-0.76 in the discovery and 0.71-0.77 in the validation cohort) and provided additional prognostic value beyond ADHERE (Acute Decompensated Heart Failure National Registry), GWTG-HF (Get With The Guidelines Heart Failure), and OPTIMIZE-HF (Δarea under the curve, 0.04-0.17) scores. Decision curve analyses showed improved net clinical benefit for mortality prediction across threshold probabilities of 12% to 35% in the discovery and 15% to 28% in the validation cohort.

conclusionsLow serum levels of lysophosphatidylethanolamine 20:4, lysophosphatidylcholine 20:4, lysophosphatidylcholine 14:0, and lysophosphatidylethanolamine 18:1 were independently associated with in-hospital mortality in acute heart failure. These findings suggest that specific lysophospholipids may serve as novel prognostic biomarkers, warranting validation in larger studies to confirm their clinical applicability.

Indexed as

Heart FailureHospital MortalityLysophospholipidsAcute DiseaseAgedAged, 80 and overBiomarkersFemaleHumansLipidomicsMaleMiddle AgedPredictive Value of TestsPrognosisProspective StudiesRisk AssessmentBiomarkersLysophospholipidsacute heart failurebiomarkerslipidomicsmass spectrometryoutcome

Identifiers

PMID41553073
PMCPMC12919526

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Registered trials

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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.