Evidence map›Paper›PMID 38994147›Full record

ArticleWorld journal of gastrointestinal oncology2024

Analysis of metabolic characteristics of metabolic syndrome in elderly patients with gastric cancer by non-targeted metabolomics.

Huan Zhang, Wen-Bing Shen, Lin Chen

Abstract read
In one paragraph

Article in World journal of gastrointestinal oncology, 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

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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. Article
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

3 authors.

Huan ZhangMedical School of Chinese PLA, Chinese PLA General Hospital, Beijing 100853, China.
Wen-Bing ShenDepartment of Gastrointestinal Surgery, Shanghai Sixth People's Hospital, Shanghai 250063, China.
Lin ChenDepartment of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China. chenlinbj@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe relationship between metabolic syndrome (MetS) and gastric cancer (GC), which is a common metabolic disease, has attracted much attention. However, the specific metabolic characteristics of MetS in elderly patients with GC remain unclear.

aimTo investigate the differentially abundant metabolites and metabolic pathways between preoperative frailty and MetS in elderly patients with GC based on nontargeted metabolomics techniques.

methodsIn this study, 125 patients with nonfrail nonmeal GC were selected as the control group, and 50 patients with GC in the frail group were selected as the frail group. Sixty-five patients with GC combined with MetS alone were included in the MetS group, and 50 patients with GC combined with MetS were included in the MetS group. Nontargeted metabolomics techniques were used to measure plasma metabolite levels by ultrahigh-performance liquid chromatography-mass spectrometry. Multivariate statistical analysis was performed by principal component analysis, orthogonal partial least squares, pattern recognition analysis, cluster analysis, and metabolic pathway annotation.

resultsA total of 125 different metabolites, including amino acids, glycerophospholipids, sphingolipids, fatty acids, sugars, nucleosides and nucleotides, and acidic compounds, were identified

conclusionElderly GC patients with simple frailty, simple combined MetS, and frailty combined with MetS have different metabolic characteristics, among which amino acid and glycerophospholipid metabolite levels are significantly lower in frail elderly GC patients, and comprehensive supplementation of fat and protein should be considered. Many kinds of metabolites, such as amino acids, lipids, nucleotides, and acidic compounds, are abnormally abundant in patients with MetS combined with fthenia, which may be related to tumor-related metabolic disorders.

Indexed as

Elderly individualsGastric cancerMetabolic syndromeNervous breakdownNontargeted metabolomics

Identifiers

PMID38994147
PMCPMC11236236

What Socratic holds

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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 Socratic graph.