Early Identification and Prognosis Prediction of Sepsis T... | NCT05305469

Studies
Early Identification and Prognosis Prediction of Sepsis Through Multiomics

NCT05305469

Sponsor

Yantai Yuhuangding Hospital

Status

Unknown status

Last Update Posted

Jan 24, 2024Actual

Enrollment

900Estimated

Phase

Not provided

Conditions

Sepsis

Interventions

Not provided

Countries

China

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Jan 2024

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Recruiting

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jan 1, 2022Actual

Primary Completion Date

Dec 31, 2024Estimated

Completion Date

Dec 31, 2025Estimated

First Submitted Date

Mar 22, 2022

First Submission Date that Met QC Criteria

Mar 22, 2022

First Posted Date

Mar 31, 2022Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Jan 22, 2024

Last Update Posted Date

Jan 24, 2024Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

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.

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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

Retention

Enrollment

900Estimated

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
GN		Gram-negative bacteria infection group
GP		Gram-positive bacteria infection group
Fungal		Fungal infection group
Viral		Viral infection group
Control		Non-sepsis group

Interventions

Not provided

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Pathogen-specific patterns	To elucidate the unique infection pathogen-specific molecular patterns in septic patients	March 2022 - December 2023

Secondary Outcomes

Measure	Description	Time Frame
Prognostic prediction models	To establish the models using multi-omics data to predict the prognosis of sepsis	March 2022 - December 2024

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

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.

Accepts Healthy Volunteers

Yes

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

85 Years

Standard Ages

AdultOlder Adult

Study Population

The study cases are from the Department of Critical Care Medicine, a top-grade hospital in Yantai

Sampling Method

Probability Sample

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Jing Wang	Contact	8605356691999	83608	wangjinghehe@sina.com

Overall Officials

Name	Affiliation	Role
Jing Wang	Yantai Yuhuangding Hospital	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Yantai Yuhuangding Hospital	Recruiting	Yantai	Shandong	264000	China

References Module

Citations

PubMed Identifier	Type	Citation	Retractions
32290837	Result	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.

ID	Term
D018805	Sepsis
D007249	Inflammation

ID	Term
D007239	Infections
D018746	Systemic Inflammatory Response Syndrome
D010335	Pathologic Processes
D013568	Pathological Conditions, Signs and Symptoms