Early Identification and Prognosis Prediction of Sepsis Through Multiomics

NCT ID: NCT05305469

Last Updated: 2024-01-24

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

900 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-01-01

Study Completion Date

2025-12-31

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Sepsis

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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GN

Gram-negative bacteria infection group

No interventions assigned to this group

GP

Gram-positive bacteria infection group

No interventions assigned to this group

Fungal

Fungal infection group

No interventions assigned to this group

Viral

Viral infection group

No interventions assigned to this group

Control

Non-sepsis group

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Patients with sepsis or septic shock who meet the diagnostic criteria (2016 sepsis 3.0 standard);
* Age 18~85 years old.

Exclusion Criteria

* ICU stay of the subjects less than 72 hours;
* Female subjects who are pregnant;
* The subjects not sure if infected;
* The subjects performed CPR;
* The subjects suffer from chronic renal disease;
* The subjects with incomplete clinical data.
Minimum Eligible Age

18 Years

Maximum Eligible Age

85 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Yantai Yuhuangding Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Jing Wang

Role: PRINCIPAL_INVESTIGATOR

Yantai Yuhuangding Hospital

Locations

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Yantai Yuhuangding Hospital

Yantai, Shandong, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Jing Wang

Role: CONTACT

8605356691999 ext. 83608

Facility Contacts

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Jing Wang

Role: primary

References

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Wang J, Sun Y, Teng S, Li K. Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation. BMC Med. 2020 Apr 15;18(1):83. doi: 10.1186/s12916-020-01546-5.

Reference Type RESULT
PMID: 32290837 (View on PubMed)

Other Identifiers

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2022-031

Identifier Type: -

Identifier Source: org_study_id

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