Evidence map›Paper›PMID 40718801›Full record

ArticleOpen medicine (Warsaw, Poland)2025

Analysis of serum metabolomics in patients with different types of chronic heart failure.

Bingzhang Jie, Qiang Li, Ling Han, Liwei Chen, Ming Yang

Abstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Bingzhang JieDepartment of Cardiology, Fuxing Hospital, Capital Medical University, Beijing, 100038, China.
Qiang LiDepartment of Pharmacology, Beijing Laboratory for Biomedical Detection Technology and Instrument, School of Basic Medical Sciences, Capital Medical University, Beijing, 100069, China.
Ling HanDepartment of Cardiology, Fuxing Hospital, Capital Medical University, Beijing, 100038, China.
Liwei ChenDepartment of Cardiology, Fuxing Hospital, Capital Medical University, Beijing, 100038, China.
Ming YangDepartment of Cardiology, Fuxing Hospital, Capital Medical University, Beijing, 100038, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Heart failure remains a major public health issue, and there are still no reliable biomarkers for left ventricular ejection fraction (LVEF). Objective: To screen for differential metabolites in the blood of HFpEF, HFmrEF, and HFrEF patients based on metabolomics analysis of their blood samples. Methods: Total 44 patients in HFpEF group, 30 patients in HFmrEF group, and 36 patients in HFrEF group were selected. The blood metabolites were analyzed by liquid chromatography high-resolution mass spectrometry and classified by principal component analysis, and then potential biomarker were screened. Partial least squares discriminant analysis was used to model and investigate the predictive ability of biomarkers for LVEF. Results: Blood metabolite profiles of HFpEF, HFmrEF, and HFrEF groups could be well distinguished, and seven potential biomarkers were identified, such as phosphatidylcholine, phosphatidylinositol, lysophosphatidylcholine, lysophosphatidylcholine, ceramide, sphingosine, and sphingomyelin. Four metabolic pathways, such as glycerol phospholipid metabolic pathway, linoleic acid metabolic pathway, purine pyrimidine metabolism pathway, and linolenic acid metabolism pathway were identified, among which glycerol phospholipid metabolism pathway was the most significant. Conclusion: The changes in glycerol phospholipid metabolism pathway may help identify HFpEF, HFmrEF, and HFrEF.

Indexed as

glycerophospholipid metabolic pathwayheart failureliquid phase high-resolution mass spectrometryLVEFmetabolome

Identifiers

PMID40718801
PMCPMC12290367

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