Evidence map›Paper›PMID 39300427›Full record

ArticleRespiratory research2024

Metabolomic characterization of COVID-19 survivors in Jilin province.

Panyang Xu, Lei Zeng, Chunyu Wang, Jiatong Chai, Junguo Yin, Jiancheng Xu

Abstract read
In one paragraph

Article in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Panyang XuDepartment of Laboratory Medicine, First Hospital of Jilin University, Changchun, China.
Lei ZengBethune Institute of Epigenetic Medicine, First Hospital of Jilin University, Changchun, Jilin, China.
Chunyu WangState Key Laboratory of Supramolecular Structure and Material Jilin University, Changchun, China.
Jiatong ChaiDepartment of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
Junguo YinDepartment of Clinical Laboratory, Changchun Hospital of Traditional Chinese Medicine, Changchun, China.
Jiancheng XuDepartment of Laboratory Medicine, First Hospital of Jilin University, Changchun, China. xjc@jlu.edu.cn.

Funding

First Hospital Translational Funding for Scientific & Technological Achievements CGZHYD202012-005Jilin Science and Technology Development Program 20190304110YY
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has escalated into a severe global public health crisis, with persistent sequelae observed in some patients post-discharge. However, metabolomic characterization of the reconvalescent remains unclear.

methodsIn this study, serum and urine samples from COVID-19 survivors (n = 16) and healthy subjects (n = 16) underwent testing via the non-targeted metabolomics approach using UPLC-MS/MS. Univariate and multivariate statistical analyses were conducted to delineate the separation between the two sample groups and identify differentially expressed metabolites. By integrating random forest and cluster analysis, potential biomarkers were screened, and the differential metabolites were subsequently subjected to KEGG pathway enrichment analysis.

resultsSignificant differences were observed in the serum and urine metabolic profiles between the two groups. In serum samples, 1187 metabolites were detected, with 874 identified as significant (457 up-regulated, 417 down-regulated); in urine samples, 960 metabolites were detected, with 39 deemed significant (12 up-regulated, 27 down-regulated). Eight potential biomarkers were identified, with KEGG analysis revealing significant enrichment in several metabolic pathways, including arginine biosynthesis.

conclusionsThis study offers an overview of the metabolic profiles in serum and urine of COVID-19 survivors, providing a reference for post-discharge monitoring and the prognosis of COVID-19 patients.

Indexed as

BiomarkersCOVID-19MetabolomicsSurvivorsAdultAgedCase-Control StudiesChinaFemaleHumansMaleMetabolomeMiddle AgedBiomarkersBiomarkersCOVID-19MetabolomicsSARS-CoV-2UPLC-MS/MS

Identifiers

PMID39300427
PMCPMC11411991

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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.