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.
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.
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.