AI-Based Precision Transfusion Prediction Model in Critically Ill Patients

NCT07762131 | Not Yet Recruiting

• 2 other identifiers: 20260140IR2025639
• Study Type: observational
• Target: 2,598
• Locations: 0 countries
• Sites: N/A

Brief Summary

This multicenter observational study aims to develop and validate an artificial intelligence-based precision transfusion prediction model for critically ill patients. The study will collect clinical characteristics, laboratory parameters, transfusion-related information, physiological data, and clinical outcomes from critically ill patients admitted to intensive care units. An AI model will be developed using retrospective data and further evaluated using prospective observational data. The primary objective is to investigate factors associated with multiple organ dysfunction syndrome (MODS) and establish a predictive model to support individualized transfusion management in critically ill patients.

Conditions

Critical Illness; Multiple Organ Dysfunction Syndrome; Blood Transfusion

Keywords

Artificial Intelligence; Precision Transfusion; Critically Ill Patients; Multiple Organ Dysfunction Syndrome

Outcome Measures

Primary Outcomes (1)

• Occurrence of Multiple Organ Dysfunction Syndrome (MODS)

  The primary outcome is the occurrence of multiple organ dysfunction syndrome (MODS) during intensive care unit hospitalization. MODS will be defined according to clinical diagnostic criteria based on dysfunction of two or more organ systems.

  During ICU hospitalization (up to 28 days after ICU admission)

Secondary Outcomes (2)

• ICU Mortality

  Up to Day 28 after ICU admission

• Hospital Mortality

  Up to Day 28 after ICU admission

Study Arms (1)

Critically Ill Patient Cohort

Other: Red Blood Cell Transfusion Exposure

Interventions

Red Blood Cell Transfusion Exposure OTHER

Red blood cell transfusion exposure refers to the receipt of red blood cell transfusion during intensive care hospitalization. Transfusion-related information, including transfusion status, number of transfused units, and cumulative transfusion volume, will be collected from routine clinical care records. Transfusion decisions are not assigned by the study protocol, and no intervention is performed as part of this observational study.

Critically Ill Patient Cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This study includes adult critically ill patients admitted to intensive care units. Clinical data including demographic characteristics, underlying diseases, severity indicators, laboratory parameters, transfusion-related information, and clinical outcomes will be collected from electronic medical records. The study population will be used to develop an artificial intelligence-based prediction model for precision transfusion management and risk assessment of multiple organ dysfunction syndrome in critically ill patients.

You may qualify if:

• Adult patients (aged ≥18 years) admitted to the intensive care unit.
• Patients with available clinical data, including demographic characteristics, laboratory parameters, transfusion-related information, and clinical outcomes.
• Patients meeting the requirements for model development and analysis.

You may not qualify if:

• Patients younger than 18 years.
• Patients with missing key clinical information required for analysis.
• Patients with repeated ICU admissions during the study period (only the first ICU admission will be included).
• Patients whose data cannot be used for research purposes according to ethical requirements.

Sponsors & Collaborators

• Second Affiliated Hospital, Zhejiang University, School of Medicine: lead

MeSH Terms

Conditions

Critical Illness; Multiple Organ Failure

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Shock

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 5, 2026
• First Posted: August 13, 2026
• Study Start: September 1, 2026
• Primary Completion (Estimated): May 1, 2029
• Study Completion (Estimated): September 1, 2029
• Last Updated: August 13, 2026

Record last verified: 2026-08

Data Sharing

• IPD Sharing: Will not share