Identifying and predicting sepsis outcomes using multiomics data

Early Identification and Prognosis Prediction of Sepsis Through Multiomics

This study is trying to see if combining different types of biological data can help doctors better predict how patients with sepsis will do based on their specific infections.

Quick facts

• Study type: Observational
• Enrollment: 900 (estimated)
• Ages: 18 Years to 85 Years
• Sex: All
• Sponsor: Yantai Yuhuangding Hospital (other)
• Locations: 1 site (Yantai, Shandong)
• Trial ID: NCT05305469 on ClinicalTrials.gov

What this trial studies

This observational study focuses on patients diagnosed with sepsis or septic shock, aiming to integrate various multi-omics data, including plasma metabolome and genetic information, to identify pathogen-specific molecular patterns. By employing multiple machine learning algorithms, the study seeks to develop prognostic prediction models that can enhance understanding of sepsis outcomes based on different infections. The research will analyze clinical indicators alongside these data to provide a comprehensive view of the patient's condition and prognosis.

Who should consider this trial

Good fit: Ideal candidates for this study are adults aged 18 to 85 who have been diagnosed with sepsis or septic shock.

Not a fit: Patients who are not diagnosed with sepsis or those with chronic renal disease may not benefit from this study.

Why it matters

Potential benefit: If successful, this study could lead to improved prognostic tools for sepsis, enabling better patient management and outcomes.

How similar studies have performed: While the integration of multi-omics data in sepsis research is a growing field, this specific approach utilizing machine learning for pathogen-specific prognostic models is relatively novel.

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.

Where this trial is running

Yantai, Shandong

• Yantai Yuhuangding Hospital — Yantai, Shandong, China (RECRUITING)

Study contacts

• Principal investigator: Jing Wang — Yantai Yuhuangding Hospital
• Study coordinator: Jing Wang

Conditions: Sepsis, Prognosis, Inflammation, Immune, Multiomics, Machine learning