5305469
Last Update Posted: 2024-01-24
Recruiting
All Genders accepted | 18 Years-85 Years |
900 Estimated Participants | No Expanded Access |
Observational Study | Accepts healthy volunteers |
Early Identification and Prognosis Prediction of Sepsis Through Multiomics
This study aims to integrate multi-omics data and clinical indicators to reveal pathogen-specific molecular patterns in patients with sepsis and establish prognostic prediction models through multiple machine learning algorithms.
This study aims to quantify the plasma metabolome, single nucleotide polymorphisms (SNPs) of exons and immunocytokines of septic patients with different pathogen infections and prognostic outcomes. Multi-omics data, cytokines, and clinical indicators will be integrated through multiple machine learning algorithms to reveal pathogen-specific molecular patterns and multi-dimensional prognostic prediction models.
Eligibility
Relevant conditions:
Sepsis
If you aren't sure if you meet the criteria above speak to your healthcare professional. Criteria may be updated but not reflected here, do not hesitate to contact the trial if you think are close to fitting criteria.
Inclusion criteria
Exclusion criteria
locations
Contact Information
Overall Contact
Jing Wang
wangjinghehe@sina.com
8605356691999
Data sourced from ClinicalTrials.gov