Evidence map›Paper›PMID 32196993›Full record

ArticleESC heart failure2020

Temporal patterns of macrophage- and neutrophil-related markers are associated with clinical outcome in heart failure patients.

Dominika Klimczak-Tomaniak, Elke Bouwens, Anne-Sophie Schuurman, K Martijn Akkerhuis, Alina Constantinescu, Jasper Brugts, B Daan Westenbrink, Jan van Ramshorst, Tjeerd Germans, Leszek Pączek and 3 more

Abstract read
In one paragraph

Article in ESC heart failure, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  12. Observational
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  14. Review
  15. Targeting of CD163International journal of molecular sciences · 2020
    Review
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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

13 authors.

Dominika Klimczak-TomaniakDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Elke BouwensDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Anne-Sophie SchuurmanDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
K Martijn AkkerhuisDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Alina ConstantinescuDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Jasper BrugtsDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
B Daan WestenbrinkDepartment of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Jan van RamshorstDepartment of Cardiology, Northwest Clinics, Alkmaar, The Netherlands.
Tjeerd GermansDepartment of Cardiology, Northwest Clinics, Alkmaar, The Netherlands.
Leszek PączekDepartment of Immunology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland.
Victor UmansDepartment of Cardiology, Northwest Clinics, Alkmaar, The Netherlands.
Eric BoersmaDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Isabella KardysDepartment of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.

Funding

Jaap Schouten FoundationNoordwest Academie
6 · The paper itself

Abstract

aimsEvidence on the association of macrophage- and neutrophil-related blood biomarkers with clinical outcome in heart failure patients is limited, and, with the exception of C-reactive protein, no data exist on their temporal evolution. We aimed to investigate whether temporal patterns of these biomarkers are related to clinical outcome in patients with stable chronic heart failure (CHF). METHODS AND

resultsIn 263 patients with CHF, we performed serial plasma measurements of scavenger receptor cysteine-rich type 1 protein M130 (CD163), tartrate-resistant acid phosphatase type 5 (TRAP), granulins (GRN), spondin-1 (SPON1), peptidoglycan recognition protein 1 (PGLYRP1), and tissue factor pathway inhibitor (TFPI). The Cardiovascular Panel III (Olink Proteomics AB, Uppsala, Sweden) was used. During 2.2 years of follow-up, we collected 1984 samples before the occurrence of the composite primary endpoint (PE) or censoring. For efficiency, we selected 567 samples for the measurements (all baseline samples, the last two samples preceding the PE, and the last sample before censoring in event-free patients). The relationship between repeatedly measured biomarker levels and the PE was evaluated by joint models. Mean (±standard deviation) age was 67 ± 13 years; 189 (72%) were men; left ventricular ejection fraction (%) was 32 ± 11. During follow-up, 70 (27%) patients experienced the PE. Serially measured biomarkers predicted the PE in a multivariable model adjusted for baseline clinical characteristics [hazard ratio (95% confidence interval) per 1-standard deviation change in biomarker]: CD163 [2.07(1.47-2.98), P < 0.001], TRAP [0.62 (0.43-0.90), P = 0.009], GRN [2.46 (1.64-3.84), P < 0.001], SPON1 [3.94 (2.50-6.50), P < 0.001], and PGLYRP1 [1.62 (1.14-2.31), P = 0.006].

conclusionsChanges in plasma levels of CD163, TRAP, GRN, SPON1, and PGLYRP1 precede adverse cardiovascular events in patients with CHF.

Indexed as

Heart FailureNeutrophilsAgedAged, 80 and overBiomarkersHumansMacrophagesMaleMiddle AgedPrognosisStroke VolumeSwedenVentricular Function, LeftBiomarkersGranulinsPeptidoglycan recognition proteinScavenger receptor cysteine-rich type 1 protein M130Spondin-1Tartrate-resistant acid phosphatase type 5

Identifiers

PMID32196993
PMCPMC7261550

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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.