SMASH-U classification: a tool for aetiology-oriented management of patients with acute haemorrhagic stroke

Intracerebral haemorrhage (ICH) is responsible for disproportionately high morbidity and mortality rates. The most used ICH classification system is based on the anatomical site. We used SMASH-U, an aetiological based classification system for ICH by predefined criteria: structural vascular lesions (S), medication (M), amyloid angiopathy (A), systemic disease (S), hypertension (H), or undetermined (U). We aimed to correlate SMASH-U classification of our patients to the intra-hospital mortality rates. We performed a single centre retrospective study at the Santa Maria Della Misericordia Hospital, Perugia (Italy) including consecutive patients between January 2009 and July 2017 assigned with 431 ICD-9 (International Classification of Diseases-9). We classified the included patients using SMASH-U criteria, and we analysed the association between SMASH-U aetiology and ICH risk factors to the outcome defined as intra-hospital mortality, using multivariable logistic regression analysis. The higher intra-hospital mortality rate was detected in the systemic disease (36.1%), medication (31.5%), and undetermined (29.4%) groups. At multivariable analysis, medication and systemic disease groups resulted associated with the outcome (odds ratio 3.47; 95% CI 1.15-10.46; P = 0.02 and 3.64; 95% CI 1.47-9.01; P = 0.005, respectively). Furthermore, age and high NIHSS at admission resulted significantly associated with intra-hospital mortality (odds ratio 1.01; 95% CI 1-1.03; P = 0.04 and 1.12; 95% CI 1.03-1.22; P = 0.008, respectively). In our retrospective study, the aetiology-oriented classification system SMASH-U showed to be potentially predictive of intra-hospital mortality of acute haemorrhagic stroke patients and it may support clinicians in the acute ICH management.

Automated summary

In this study, the use of SMASH-U classification system for ICH patients revealed that systemic disease and medication groups were associated with intra-hospital mortality rates, while age and high NIHSS at admission were also significantly associated with mortality. The study suggests that the aetiology-oriented classification system may help predict intra-hospital mortality in acute haemorrhagic stroke patients and support clinicians in management.