Why the study?
Can computed tomography imaging-based morphological features predict late adverse events in patients with acute uncomplicated Stanford type-B aortic dissection?
Can computed tomography imaging-based morphological features predict late adverse events in patients with acute uncomplicated Stanford type-B aortic dissection?
CT imaging features can be combined into a prediction model to identify patients at high risk for late adverse events following uncomplicated type-B aortic dissection.
May support CT-based risk stratification in uncomplicated type B aortic dissection; leaves open prospective validation before clinical adoption.
Computed tomography imaging-based morphological features combined into a prediction model may be able to identify patients at high risk for late adverse events after an initially uncomplicated type-B aortic dissection.
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Sailer et al. (2017) studied this question.
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