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Updated: Aug 18, 2026

Intrastriatal Injection of Autologous Blood or Clostridial Collagenase as Murine Models of Intracerebral Hemorrhage
Published on: July 3, 2014
SMASH-U aetiological classification: A predictor of long-term functional outcome after intracerebral haemorrhage
Yuchao Jia1, Guo Li1, Guini Song1
1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background:
SMASH-U is a systematic aetiological classification system for intracerebral haemorrhage (ICH) proven to be a predictor of post-ICH haematoma expansion and mortality. However, its role in predicting functional outcome remains elusive. Therefore, we aimed to investigate whether SMASH-U is associated with long-term functional outcome after ICH and improves the accuracy of prediction when added to max-ICH score.
Methods:
Consecutive acute ICH patients from 2012 to 2018 from the neurology department of Tongji Hospital were enrolled. ICH aetiology was classified according to the SMASH-U system. The association of SMASH-U with 12-month functional outcome after ICH and the predictive value were evaluated.
Results:
Of 1938 ICH patients, the aetiology of 1295 (66.8%) patients were classified as hypertension, followed by amyloid angiopathy (n = 250, 12.9%), undetermined (n = 159, 8.2%), structural lesions (n = 149, 7.7%), systemic disease (n = 74, 3.8%) and medication (n = 11, 0.6%). The baseline characteristics were different among the six aetiologies. In multivariate analysis, SMASH-U was proven to be a predictor of 12-month unfavourable functional outcome. When adding the SMASH-U system, the predictive performance of max-ICH score was improved (area under the receiver operating characteristic curve from 0.802 to 0.812, p = 0.010) and the predictive accuracy was enhanced (integrated discrimination improvement [IDI]: 1.60%, p < 0.001; continuous net reclassification improvement [NRI]: 28.16%, p < 0.001; categorical NRI: 3.34%, p = 0.004).
Conclusions:
SMASH-U predicted long-term unfavourable functional outcomes after acute ICH and improved the accuracy of prediction when added to max-ICH score. Integrating the aetiology to a score model to predict the post-ICH outcome may be meaningful and worthy of further exploration.
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