Evidence map›Paper›PMID 37827514›Full record

Observational studyJournal of proteome research2024

Metabolomics Meets Clinics: A Multivariate Analysis of Plasma and Urine Metabolic Signatures in Pulmonary Arterial Hypertension.

Renata Wawrzyniak, Peter Grešner, Ewa Lewicka, Szymon Macioszek, Artur Furga, Bożena Zieba, Michał J Markuszewski, Alicja Da Browska-Kugacka

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Journal of proteome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.6field-weighted citation impact, top 9% of its field
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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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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

8 authors at 1 institution in 1 country.

Renata WawrzyniakDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.ORCID 0000-0002-0763-4589
Peter GrešnerLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dȩbinki 1, 80-211 Gdańsk, Poland.
Ewa LewickaDepartment of Cardiology and Electrotherapy, Medical University of Gdansk, Debinki 7, 80-210 Gdańsk, Poland.
Szymon MacioszekDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.
Artur FurgaDepartment of General, Endocrine and Transplant Surgery, Invasive Medicine Center, Medical University of Gdańsk, 80-214 Gdańsk, Poland.
Bożena ZiebaFirst Department of Cardiology, Medical University of Gdansk, Smoluchowskiego 17, 80-214 Gdańsk, Poland.
Michał J MarkuszewskiDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.
Alicja Da Browska-KugackaDepartment of Cardiology and Electrotherapy, Medical University of Gdansk, Debinki 7, 80-210 Gdańsk, Poland.
Gdańsk Medical University · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary arterial hypertension (PAH) is a severe, multifactorial, and frequently misdiagnosed disorder. The aim of this observational study was to compare the plasma and urine metabolomic profiles of PAH patients and healthy control subjects. Plasma and urine metabolomic profiles were analyzed using the GC-MS technique. Correlations between metabolite levels and clinical parameters among PAH patients, as well as the between-group differences, were evaluated. The linear discriminant analysis model, which allows for subject classification in terms of PAH with the highest possible precision, was developed and proposed. Plasma pyruvic acid, cholesterol, threonine, urine 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid, butyric acid, 1,2-benzenediol, glucoheptonic acid, and 2-oxo-glutaric acid were found to build a relatively accurate classification model for PAH patients. The model reached an accuracy of 91% and significantly improved subject classification (OR = 119 [95% CI: 20.3-698.3],

Indexed as

MetabolomicsAdultAgedBiomarkersCase-Control StudiesDiscriminant AnalysisFemaleGas Chromatography-Mass SpectrometryHumansHypertension, PulmonaryMaleMetabolomeMiddle AgedMultivariate AnalysisPulmonary Arterial HypertensionBiomarkersmetabolomicsmultivariate analysisplasmapulmonary arterial hypertensionurine

Identifiers

PMID37827514
PMCPMC11302416
OpenAlexW4387566753

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.