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The modified Hijdra scale for prediction of delayed cerebral infarcts after subarachnoid hemorrhage
Vasilis Kola1, Prabin Basnet2, Viktor Horst1,3
1Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Delayed cerebral ischemia (DCI) occurs several days after subarachnoid hemorrhage (SAH) and could therefore be mitigated by treatment intervention. As testament to the great challenge of designing effective trials, however, the prevalence and severity of DCI have remained unchanged for decades. A critical need in the development of novel prophylactic treatments is optimizing initial prediction for DCI, since improved risk stratification based on prognosis could increase the statistical power of randomized trials, thereby increasing the probability of success and reducing costs. The primary objective of this study, using secondary analysis of data from the DISCHARGE-1 trial, was to evaluate the power of initial variables (medical history, clinical examination, and pre-interventional CT) for predicting the volume of delayed infarcts in SAH survivors. In multivariate analysis of 164 early survivors with pre-interventional CT within 72 h of the initial hemorrhage, the modified Hijdra scale (mHS; β = -0.016, p < 0.001) was the only independent predictor of infarct volume due to DCI, outperforming common clinical scores und manually segmented hemorrhage volumes. Furthermore, early brain injury (EBI) volume identified high-risk patients for early death early on. Thus, we propose a combined approach using mHS and EBI volume for early risk stratification in randomized trials targeting DCI.
Delayed cerebral ischemia (DCI) occurs several days after subarachnoid hemorrhage (SAH) and could therefore be mitigated by treatment intervention. As testament to the great challenge of designing effective trials, however, the prevalence and severity of DCI have remained unchanged for decades. A critical need in the development of novel prophylactic treatments is optimizing initial prediction for DCI, since improved risk stratification based on prognosis could increase the statistical power of randomized trials, thereby increasing the probability of success and reducing costs. The primary objective of this study, using secondary analysis of data from the DISCHARGE-1 trial, was to evaluate the power of initial variables (medical history, clinical examination, and pre-interventional CT) for predicting the volume of delayed infarcts in SAH survivors. In multivariate analysis of 164 early survivors with pre-interventional CT within 72 h of the initial hemorrhage, the modified Hijdra scale (mHS; β = -0.016, p < 0.001) was the only independent predictor of infarct volume due to DCI, outperforming common clinical scores und manually segmented hemorrhage volumes. Furthermore, early brain injury (EBI) volume identified high-risk patients for early death early on. Thus, we propose a combined approach using mHS and EBI volume for early risk stratification in randomized trials targeting DCI.
