Blood Transfusion, Critical Illness, Multiple Organ Dysfunction Syndrome
Conditions
Keywords
Artificial Intelligence, Precision Transfusion, Critically Ill Patients, Multiple Organ Dysfunction Syndrome
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.
Detailed description
Critically ill patients frequently require red blood cell transfusion during intensive care. However, transfusion decisions based solely on conventional indicators may not fully reflect individual differences in disease severity, oxygen delivery, and risk of organ dysfunction. Unnecessary transfusion may increase the risk of adverse outcomes, whereas delayed transfusion may worsen tissue hypoxia. This multicenter observational study aims to establish an artificial intelligence-based precision transfusion prediction model for critically ill patients. The study includes retrospective model development and prospective observational validation phases. Clinical data including demographic characteristics, underlying diseases, laboratory parameters, physiological variables, transfusion records, severity scores, organ function indicators, and clinical outcomes will be collected. Machine learning approaches will be applied to identify important predictors associated with multiple organ dysfunction syndrome (MODS) and transfusion-related outcomes. The developed model will be evaluated based on predictive performance, including discrimination, calibration, and clinical applicability. This study aims to provide an individualized risk assessment approach to improve transfusion decision-making and facilitate precision management in critically ill patients.
Interventions
OTHERRed Blood Cell Transfusion Exposure
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.
Sponsors
Second Affiliated Hospital, Zhejiang University, School of Medicine
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
* 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.
Exclusion criteria
* 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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Occurrence of Multiple Organ Dysfunction Syndrome (MODS) | During ICU hospitalization (up to 28 days after ICU admission) | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| ICU Mortality | Up to Day 28 after ICU admission | Death occurring during the intensive care unit stay. |
| Hospital Mortality | Up to Day 28 after ICU admission | Death occurring during the index hospitalization |
Outcome results
None listed