Identifying early predictive and diagnostic biomarkers and exploring metabolic pathways for sepsis after trauma based on an untargeted metabolomics approach
Abstract Systemic inflammatory response syndrome (SIRS) and organ dysfunction make it challenging to predict which major trauma patients are at risk of developing sepsis. Additionally, the unclear pathogenesis of sepsis after trauma contributes to its high morbidity and mortality. Identifying early...
Saved in:
| Main Authors: | Yi Gou, Bo-Hui Lv, Jun-Fei Zhang, Sheng-Ming Li, Xiao-Ping Hei, Jing-Jing Liu, Lei Li, Jian-Zhong Yang, Ke Feng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-92631-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Identifying biomarkers distinguishing sepsis after trauma from trauma-induced SIRS based on metabolomics data: a retrospective study
by: Yi Gou, et al.
Published: (2025-04-01) -
Distinct metabolomic signatures in allergic rhinitis with concurrent chronic spontaneous urticaria: an untargeted metabolomics analysis reveals novel biomarkers and pathway alterations
by: Xiaohong Lyu, et al.
Published: (2025-06-01) -
Impact of trauma level designation on mortality in trauma patients with sepsis: an observational study across US trauma centers
by: Ralphe Bou Chebl, et al.
Published: (2025-08-01) -
Untargeted metabolomics reveal the corrective effects of scorpion on epileptic mice
by: Lele Li, et al.
Published: (2025-01-01) -
Predictors of sepsis in trauma patients: a National Trauma Data Bank analysis
by: Ralphe Bou Chebl, et al.
Published: (2024-12-01)