Evidence map›Paper›PMID 40144016›Full record

ArticleJHLT open2023

Plasma VEGF-D and sFLT-1 are potential biomarkers of hemodynamics and congestion in heart failure and following heart transplantation.

Salaheldin Ahmed, Jakob Lundgren, Abdulla Ahmed, Göran Rådegran

Abstract read
In one paragraph

Article in JHLT open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

4 authors.

Salaheldin AhmedDepartment of Clinical Sciences Lund, The Section for Cardiology, Lund University, Lund, Sweden.
Jakob LundgrenDepartment of Clinical Sciences Lund, The Section for Cardiology, Lund University, Lund, Sweden.
Abdulla AhmedDepartment of Clinical Sciences Lund, The Section for Cardiology, Lund University, Lund, Sweden.
Göran RådegranDepartment of Clinical Sciences Lund, The Section for Cardiology, Lund University, Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inflammation and tyrosine-kinases are known mediators in the pathobiology of cardiovascular disease. Plasma biomarkers reflecting these systems may provide a noninvasive complement reflecting hemodynamics, aiding in clinical decision-making. We therefore aimed to investigate the plasma levels of vascular and inflammatory proteins, and their associations with invasive hemodynamics in advanced heart failure (HF) before, and at multiple follow-ups after heart transplantation (HT). Methods: Using multiplex sandwich immunoassays, absolute plasma concentrations of 9 vascular and inflammatory proteins were assessed in 26 patients with advanced HF, before HT, and at 4 weeks, 6 months, and 1year after HT. Right heart catheterization hemodynamics were assessed at the time of blood sampling. Repeated measures correlations were performed to evaluate the overall intra-individual development of plasma protein levels in relation to hemodynamics' development over time. Results: Out of 9 proteins included initially, in advanced HF, elevated plasma levels of vascular endothelial growth factor D (VEGF-D) and soluble fms-like tyrosine kinase-1 (sFlt-1) decreased most markedly at 4 weeks ( Conclusions: In advanced HF, elevated plasma VEGF-D and sFlt-1 levels decrease early, already within 4 weeks after HT, and further throughout the first year postoperatively. Our findings support that high plasma VEGF-D and sFlt-1 concentrations before HT are related to congestion and overall hemodynamic improvement. Plasma VEGF-D and sFlt-1 may consequently be potential noninvasive biomarkers for monitoring hemodynamic deterioration and congestion in HF, and surveillance after HT.

Indexed as

heart failureheart transplantationpulmonary hypertensionright heart catheterizationtyrosine kinases

Identifiers

PMID40144016
PMCPMC11935418

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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.