ArticleInternational journal of molecular sciences2025
Metabolomic Signatures Predict Seven-Year Mortality in Clinically Stable COPD Patients.
Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Correction: Enríquez-Rodríguez et al. Metabolomic Signatures Predict Seven-Year Mortality in Clinically Stable COPD Patients.International journal of molecular sciences · 2025Article
- Circulating metabolome as key biomarkers for ventilator-associated pneumonia: Case-Control study in a tertiary care hospital of North India.International journal of critical illness and injury scienceArticle
Corrections and comments
- Erratum issued
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a complex condition with high mortality. Early identification of patients at increased risk of death remains a major clinical challenge. This pilot study aimed to explore whether plasma metabolomic profiling could aid in the prediction of long-term (7-year) mortality and provide insight into potential underlying mechanisms. Plasma samples from 54 randomly selected stable COPD patients were analyzed using both untargeted and semi-targeted LC-MS approaches. After excluding patients with unclear death data, non-COPD-related deaths and metabolomic outliers, 41 individuals were included in the final analysis. During follow-up, 13 patients (32%) died, and 28 survived. Univariate analysis identified 12 metabolites-mainly amino acids-that differed significantly between the two groups. Functional analysis suggested a significant disruption in energy production pathways. Predictive models developed using machine learning algorithms, consisting of either ten metabolites alone or nine metabolites plus FEV
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