An observational study in Critical Illness, Multiple Organ Dysfunction Syndrome and Blood Transfusion, sponsored by Second Affiliated Hospital, Zhejiang University, School of Medicine. Not yet recruiting. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-08-13.
Sponsored by Second Affiliated Hospital, Zhejiang University, School of Medicine · Observational
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.
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.
193 studies on the registry are indexed under Multiple Organ Failure; 47 are open to participants now.
This study's planned enrollment of 2,598 is above the median of 200 across 94 observational studies indexed under Multiple Organ Failure.
Browse Multiple Organ Failure studies →Second Affiliated Hospital, Zhejiang University, School of Medicine is the lead sponsor of 99 studies on the registry; 67 are open to participants now.
Compared within Multiple Organ Failure, this study's primary condition as ClinicalTrials.gg classifies it; the registry's first condition term is Critical Illness. The counts are of registry records indexed under each term, refreshed daily. How we classify →
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.
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Exclusion Criteria:
Other: Red 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.
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.
Time frame: During ICU hospitalization (up to 28 days after ICU admission)
ICU Mortality
Death occurring during the intensive care unit stay.
Time frame: Up to Day 28 after ICU admission
Hospital Mortality
Death occurring during the index hospitalization
Time frame: Up to Day 28 after ICU admission
No study locations are listed for this record.
Plan to share: No
No publications or documents are linked to this record.
This study is not yet recruiting, as verified in Aug 2026. You cannot join it, but the record below documents what was studied.
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Second Affiliated Hospital, Zhejiang University, School of Medicine