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Updated: Aug 6, 2026
Real-Time High Throughput Technique to Quantify Neutrophil Extracellular Traps Formation in Human Neutrophils
Published on: December 1, 2023
Development of a Predictive Model for Transfusion-Related Acute Lung Injury Based on Neutrophil Extracellular Traps
Qiong Wang1, Zhenyang Li2, Junliang Shao1
1Department of Blood Transfusion, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214023, China, njmu.edu.cn.
Transfusion-related acute lung injury (TRALI) risk in massive hemorrhage patients is linked to neutrophil extracellular traps (NETs). Biomarkers like citrullinated histone H3 (citH3), myeloperoxidase (MPO), and neutrophil elastase (NE) can predict TRALI early.
Area of Science:
- Critical Care Medicine
- Hematology
- Pulmonology
Background:
- Massive transfusion in acute hemorrhage poses a risk of transfusion-related acute lung injury (TRALI).
- Neutrophil extracellular traps (NETs) are implicated in acute lung injury pathogenesis.
- Early identification of TRALI risk is crucial for timely intervention.
Purpose of the Study:
- To investigate the association between NETs and TRALI in patients undergoing massive transfusion.
- To develop a machine learning-based predictive model for early TRALI detection.
Main Methods:
- A multicenter prospective study involving 513 patients with acute massive hemorrhage.
- Comparison of clinical features and NET-related markers between TRALI-injured and uninjured groups.
- Utilized LASSO regression and random forest for variable selection and importance ranking, followed by multivariate logistic regression and nomogram construction.
Main Results:
- Patients who developed TRALI had higher rates of smoking history, transfusion volume, and frequency.
- Elevated levels of citrullinated histone H3 (citH3), myeloperoxidase (MPO), neutrophil elastase (NE), and inflammatory cytokines were observed in the injured group.
- Multivariate analysis identified citH3, MPO, and NE as independent predictors of TRALI, with a combined model achieving an AUC of 0.85.
Conclusions:
- TRALI risk in massive hemorrhage patients is significantly associated with NET-related markers, specifically citH3, MPO, and NE.
- A predictive model incorporating these biomarkers enables valuable early identification of TRALI.
- This model can aid clinical decision-making for improved patient outcomes.
