Development of a Predictive Model for Transfusion-Related Acute Lung Injury Based on Neutrophil Extracellular Traps (NETs).

Authors

Qiong Wang, Zhenyang Li, Junliang Shao, Xinchen Qiang, Wen Gong, Lingling Sun, Huaying Yang, Zhen Li, Junfang Wang

Published in

Mediators of inflammation. Volume 2026. Issue 1. Pages e7778073.

Abstract

Patients receiving massive transfusion after acute hemorrhage are at risk for transfusion-related acute lung injury (TRALI), a severe complication. Neutrophil extracellular traps (NETs) play a key role in acute lung injury. This study aimed to explore the link between NETs and TRALI and to develop a risk-prediction model using machine learning for early detection and intervention.
In this multicenter prospective study, 513 patients with acute massive hemorrhage who underwent transfusion therapy (March 2020-February 2025) were consecutively recruited. All biomarker assays, sampling time points, and the statistical analysis plan were prespecified and ethically approved before study initiation. Based on TRALI occurrence after transfusion, they were divided into an injured group (n = 42) and a uninjured group (n = 471). Clinical features and NET-related markers were compared. LASSO regression was used for variable selection, followed by random forest for importance ranking. Multivariate logistic regression identified independent predictors, and a nomogram model was built and evaluated using ROC analysis, calibration, and decision curve analysis.
The injured group had significantly higher rates of smoking history, total infusion volume, perioperative transfusion volume, and transfusion frequency (all p < 0.05). Levels of citrullinated histone H3 (citH3), myeloperoxidase (MPO), neutrophil elastase (NE), interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and interleukin-8 (IL-8) were also elevated (all p < 0.05). LASSO identified seven key variables, with citH3 and MPO showing high importance. Multivariate analysis confirmed citH3 (OR = 1.142), MPO (OR = 5.017), and NE (OR = 1.014) as independent predictors of TRALI (all p < 0.05). The combined model achieved an AUC of 0.85 (95% CI: 0.78-0.92), indicating strong predictive performance.
TRALI risk in acute massive hemorrhage patients is associated with NET-related markers, particularly citH3, MPO, and NE. A model integrating these indicators provides valuable early identification of TRALI, aiding clinical decision-making.

PMID:
42478331
Bibliographic data and abstract were imported from PubMed on 21 Jul 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.