Neurology: MrI characteristics of cerebrovascular disease do not improve the ability to predict stroke outcomes

The number of people worldwide who have survived a stroke is increasing.
to quickly predict post-stroke outcomes is critical to the management of these patients.
small cerebrovascular disease (SVD) has attracted the attention of researchers because it can affect clinical outcomes by disrupting the plasticity of neural networks and neurons.
SVD scores have increasingly been used to assess the overall severity of SVD, including white matter high signal lesions (WMH), fissures (lacune), space around blood vessels (PVS), and cerebral micro-bleeding (CMBs).
although it has been found that brain SVD has been shown to be associated with clinical outcomes, it is not clear whether it actually provides predictive results for stroke.
, of the University of Bordeaux in France, assessed the prognosto-value of SVD scores in terms of functional, cognitive and psychological outcomes after stroke.
Based on forward-looking longitudinal cohorts, they included two data sets: 428 and 197 patients with initial stroke, and collected MRIs 24 to 72 hours after stroke, quantifying WMH, lacune, PVS, CMB, and atrophy.
to assess functional, cognitive, and psychological states during follow-up over a period of 3-6 months.
the predictive accuracy of age, baseline NIH stroke scale score (NIHSS) and infarction volume (model 1) was quantified on data set 1, the total score of SVD (model 2) was added, and the improvement of prediction accuracy was evaluated.
two models are also applied to dataset 2 to see if the results of dataset 1 can be repeated.
, in Model 3, the MRI characteristics of SVD are added instead of the SVD total score.
results showed that Model 1 performed well in distinguishing between poor and good functional outcomes (AUC 0.915) and generally in identifying patients with cognitive impairment and depression (AUC was 0.750 and 0.688, respectively).
SVD score is associated with poor results (OR=1.30, P=0.0090, best performed in functional results).
, adding A total score of SVD (Model 2) or a single MRI feature (Model 3) does not improve the prediction than Model 1.
results for dataset 2 are similar.
the significance of this study is that SVD was found to be independently associated with functional, cognitive and psychological outcomes, but had no additional clinical significance in predicting outcomes in stroke patients compared to conventional predictors such as age and baseline NIHSS.
origin of the original Cerebral Small Vessel Disease MRI Features Do Not Improve the Prediction of Stroke Outcome; Juliette Coutureau, et al. Neurology Jan 2021, 96 (4) e527-e537; DOI: 10.1212/WNL.000000000011208 Freeman Source: MedSci Original Copyright Notice: All noted on this website "Source: Metz Medicine" or "Source: MedSci Original" text, images and audio and video materials, copyrights are owned by Metz Medical, without authorization, no media, website or individual may reproduce, authorized to reproduce with the words "Source: Mets Medicine".
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