Transfusion‐related acute lung injury not a two‐hit, but a multicausal model

RA Middelburg, JG van der Bom - Transfusion, 2015 - Wiley Online Library
RA Middelburg, JG van der Bom
Transfusion, 2015Wiley Online Library
Background The etiology of transfusion‐related acute lung injury (TRALI) is often referred to
as a “two‐hit model,” the first hit being patient predisposition and the second being a
transfusion. This model lumps all patient‐related risk factors together and thereby may
hamper identification of individual, potentially preventable or modifiable risk factors. Study
design and methods Like any disease, TRALI is multicausal in nature. To be able to
effectively scrutinize all contributing causes, we need to clearly describe this multicausality …
Background
The etiology of transfusion‐related acute lung injury (TRALI) is often referred to as a “two‐hit model,” the first hit being patient predisposition and the second being a transfusion. This model lumps all patient‐related risk factors together and thereby may hamper identification of individual, potentially preventable or modifiable risk factors.
Study design and methods
Like any disease, TRALI is multicausal in nature. To be able to effectively scrutinize all contributing causes, we need to clearly describe this multicausality as completely as possible. Several models are already commonly used to describe the multicausality of other diseases, including threshold models and the sufficient cause model.
Results
Here we describe the application of two different multicausal models to TRALI. These models can readily describe any potential scenario for the etiology of TRALI. First we will introduce the intuitively appealing threshold model, which shows some similarities with the Bux and Sachs threshold model for TRALI. Second we discuss the more abstract sufficient cause model.
Conclusions
Both models have their strengths and limitations. Both are, however, better equipped than the two‐hit model to describe the multicausal nature of TRALI. Further identification of all involved risk factors and the complex interplay between them is facilitated by these models.
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