EIPPSM: Early Identification and Prognosis Prediction of Sepsis Through Multiomics
Study Details
Study Description
Brief Summary
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.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
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.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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GN Gram-negative bacteria infection group |
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GP Gram-positive bacteria infection group |
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Fungal Fungal infection group |
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Viral Viral infection group |
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Control Non-sepsis group |
Outcome Measures
Primary Outcome Measures
- Pathogen-specific patterns [March 2022 - December 2023]
To elucidate the unique infection pathogen-specific molecular patterns in septic patients
Secondary Outcome Measures
- Prognostic prediction models [March 2022 - December 2024]
To establish the models using multi-omics data to predict the prognosis of sepsis
Eligibility Criteria
Criteria
Inclusion Criteria:
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Patients with sepsis or septic shock who meet the diagnostic criteria (2016 sepsis 3.0 standard);
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Age 18~85 years old.
Exclusion Criteria:
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ICU stay of the subjects less than 72 hours;
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Female subjects who are pregnant;
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The subjects not sure if infected;
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The subjects performed CPR;
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The subjects suffer from chronic renal disease;
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The subjects with incomplete clinical data.
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | Yantai Yuhuangding Hospital | Yantai | Shandong | China | 264000 |
Sponsors and Collaborators
- Yantai Yuhuangding Hospital
Investigators
- Principal Investigator: Jing Wang, Yantai Yuhuangding Hospital
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- 2022-031