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Research on the AI-powered Multi-modal Data Fusion Model for Accurate Classification and Dynamic Warning of Sepsis

Research on the AI-powered Multi-modal Data Fusion Model for Accurate Classification and Dynamic Warning of Sepsis

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600127509
Enrollment
Unknown
Registered
2026-07-01
Start date
2026-07-01
Completion date
Unknown
Last updated
2026-07-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Sepsis

Interventions

Observation group:None

Sponsors

Affiliated Hospital of Guangdong Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Age between 18 and 80; 2. Admitted to the ICU of the hospital during the study; 3. Patients diagnosed with sepsis according to the 'Chinese Expert Consensus on Early Prevention and Blocking of Sepsis in Emergency Departments'

Exclusion criteria

Exclusion criteria: 1.The clinical data is incomplete; 2.Do not agree to participate in this study;

Design outcomes

Primary

MeasureTime frame
Risk of death in sepsis patients;—

Secondary

MeasureTime frame
Other clinical outcomes for sepsis patients, like complications or readmission to the ICU;—

Countries

China

Contacts

Public ContactJiayuan Wu

Affiliated Hospital of Guangdong Medical University

87537665@qq.com+86 759 238 7156

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 23, 2026