Evidence map›Paper›PMID 39390047›Full record

ArticleScientific reports2024

Metabolomic profiling of COVID-19 using serum and urine samples in intensive care and medical ward cohorts.

Ana Isabel Tristán, Cristina Jiménez-Luna, Ana Cristina Abreu, Francisco Manuel Arrabal-Campos, Ana Del Mar Salmerón, Firma Isabel Rodríguez, Manuel Ángel Rodríguez Maresca, Antonio Bernardino García, Consolación Melguizo, Jose Prados and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
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  5. MTHFR allele and one-carbon metabolic profile predict severity of COVID-19.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

11 authors.

Ana Isabel Tristán *Department of Chemistry and Physics, Research Centre CIAIMBITAL, University of Almería, Ctra. Sacramento, s/n, 04120, Almería, Spain.
Cristina Jiménez-Luna *Biosanitary Research Institute of Granada (ibs.GRANADA), 18014, Granada, Spain.
Ana Cristina AbreuDepartment of Chemistry and Physics, Research Centre CIAIMBITAL, University of Almería, Ctra. Sacramento, s/n, 04120, Almería, Spain.
Francisco Manuel Arrabal-CamposDepartment of Engineering, CeiA3, University of Almería, Ctra. Sacramento, s/n, 04120, Almería, Spain.
Ana Del Mar SalmerónDepartment of Chemistry and Physics, Research Centre CIAIMBITAL, University of Almería, Ctra. Sacramento, s/n, 04120, Almería, Spain.
Firma Isabel RodríguezTorrecárdenas University Hospital, 04009, Almería, Spain.
Manuel Ángel Rodríguez MarescaTorrecárdenas University Hospital, 04009, Almería, Spain.
Antonio Bernardino GarcíaTorrecárdenas University Hospital, 04009, Almería, Spain.
Consolación MelguizoBiosanitary Research Institute of Granada (ibs.GRANADA), 18014, Granada, Spain.
Jose PradosBiosanitary Research Institute of Granada (ibs.GRANADA), 18014, Granada, Spain. jcprados@ugr.es.
Ignacio FernándezDepartment of Chemistry and Physics, Research Centre CIAIMBITAL, University of Almería, Ctra. Sacramento, s/n, 04120, Almería, Spain. ifernan@ual.es.

Funding

Gobierno de España MCIN/AEI/10.13039/501100011033 and Unión Europea "Next Generation EU"/PRTR PDC2021-121248-I00, PLEC2021-007774 and CPP2022-009967Junta de Andalucía PREDOC_01024State Research Agency of the Spanish Ministry of Science and Innovation PID2021-126445OB-I00
6 · The paper itself

Abstract

The COVID-19 pandemic remains a significant global health threat, with uncertainties persisting regarding the factors determining whether individuals experience mild symptoms, severe conditions, or succumb to the disease. This study presents an NMR metabolomics-based approach, analysing 80 serum and urine samples from COVID-19 patients (34 intensive care patients and 46 hospitalized patients) and 32 from healthy controls. Our research identifies discriminant metabolites and clinical variables relevant to COVID-19 diagnosis and severity. These discriminant metabolites play a role in specific pathways, mainly "Phenylalanine, tyrosine and tryptophan biosynthesis", "Phenylalanine metabolism", "Glycerolipid metabolism" and "Arginine and proline metabolism". We propose a three-metabolite diagnostic panel-comprising isoleucine, TMAO, and glucose-that effectively discriminates COVID-19 patients from healthy individuals, achieving high efficiency. Furthermore, we found an optimal biomarker panel capable of efficiently classify disease severity considering both clinical characteristics (obesity/overweight, dyslipidemia, and lymphocyte count) together with metabolites content (ethanol, TMAO, tyrosine and betaine).

Indexed as

BiomarkersCOVID-19MetabolomicsAdultAgedCohort StudiesCritical CareFemaleHumansIntensive Care UnitsMaleMetabolomeMiddle AgedSARS-CoV-2Severity of Illness IndexBiomarkersBiomarkersCOVID-19MetabolomicsNMRSerumUrine

Identifiers

PMID39390047
PMCPMC11467386

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.