Evidence map›Paper›PMID 41724744›Full record

ArticleScientific reports2026

Longitudinal and cross-sectional associations of myocardial stress markers with kidney function and chronic kidney disease in the BiomarCaRE project.

Jie-Sheng Lin, Tanja Zeller, Wolfgang Koenig, Pekka Jousilahti, Frank Kee, Licia Iacoviello, Hugh Tunstall-Pedoe, Stefan Söderberg, Giancarlo Cesana, Luigi Palmieri and 9 more

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Article in Scientific reports, 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

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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

19 authors.

Jie-Sheng LinInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Tanja ZellerInstitute for Cardiogenetics, University of Lübeck, University Hospital Schleswig-Holstein, Lübeck, Germany.
Wolfgang KoenigGerman Heart Center, Munich, Technical University of Munich, Munich, Germany.
Pekka JousilahtiDepartment of Public Health, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.
Frank KeeCentre for Public Health, Queen's University Belfast, Belfast, Northern Ireland, UK.
Licia IacovielloDepartment of Epidemiology and Prevention, IRCCS Neuromed, Pozzilli, Italy.
Hugh Tunstall-PedoeCardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, Dundee, Scotland.
Stefan SöderbergDepartment of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Giancarlo CesanaDepartment of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.
Luigi PalmieriDepartment of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore Di Sanità-ISS, Rome, Italy.
Veikko SalomaaDepartment of Public Health, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.
Julia de Man LapidothDepartment of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Roberto De PontiResearch Center in Epidemiology and Preventive Medicine (EPIMED), Department of Medicine and Surgery, University of Insubria, Varese, Italy.
Chiara DonfrancescoDepartment of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore Di Sanità-ISS, Rome, Italy.
Thiess LorenzGerman Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Lübeck, Germany.
Kari KuulasmaaDepartment of Public Health, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.
Stefan BlankenbergGerman Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Lübeck, Germany.
Annette PetersInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Barbara ThorandInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany. barbara.thorand@helmholtz-munich.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the complex relationship between cardiovascular disease (CVD) and chronic kidney disease (CKD), CVD-related markers may serve as CKD biomarkers. We examined associations of three major CVD-markers [mid-regional pro-adrenomedullin (MR-proADM), MR-pro-atrial natriuretic peptide (MR-proANP), and N-terminal pro-B-type natriuretic peptide (NT-proBNP)] with CKD. Cross-sectional analyses included up to 61,830 participants, and longitudinal analyses (NT-proBNP only) 4205 individuals. Kidney function was assessed by estimated glomerular filtration rate (eGFR) using creatinine, cystatin C, or both (eGFRcr-cys). Markers were categorized into four groups. Cross-sectional analyses found that higher levels of all three markers were consistently associated with lower eGFR and higher CKD prevalence. For example, per 1 standard deviation (SD) increase in log-transformed NT-proBNP, corresponding to a 2.71-fold increase in the original concentration, was associated with -2.35 (-2.49, -2.21) ml/min/1.73m

Indexed as

KidneyMyocardiumRenal Insufficiency, ChronicAdrenomedullinAgedAtrial Natriuretic FactorBiomarkersCardiovascular DiseasesCross-Sectional StudiesCystatin CFemaleGlomerular Filtration RateHumansLongitudinal StudiesMaleMiddle AgedAdrenomedullinAtrial Natriuretic FactorBiomarkersCystatin CNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)Protein PrecursorsChronic kidney diseaseKidney functionMR-proADMMR-proANPNT-proBNP

Identifiers

PMID41724744
PMCPMC12929796

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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.