Use of CT-Scan for Predicting Mortality of Acute Intracerebral Haemorrhagic Stroke within 7 and 28 Days

Abstract

Background: Recognition of factors affecting morbidity and mortality of a disease helps in the proper management of a disease. CT scan of Brain is an essential investigation for all stroke patients. Identifying different characteristics of the CT findings of stroke patients which affect morbidity and mortality will help in the specific management of stroke patients. Thus this study was done to identify such factors from CT scan of Brain which will help in the proper management of stroke patients.
 Objectives: The aim of this present study was to determine the 7th and 28th days’ mortality rate of acute intracerebral hemorrhagic stroke and to determine the predictors of mortality.
 Methodology: Consecutive CT scan proven stroke patients following ICH were studied in the department of Radiology & Imaging at Rajshahi Medical College, Rajshahi, Bangladesh in collaboration with the Department of Neurology of Rajshahi Medical College, Rajshahi from January 2012 to December 2013. Site, size and volume of haematoma, midline shift, pineal gland displacement, hydrocephalus and intraventricular extension of haemorrhage were correlated with the mortality within 7th and 28th days of acute stroke. Risk factors like hypertension, smoking, diabetes and alcoholism were also recorded.
 Result: Ninety-nine consecutive CT scan proven stroke patients following ICH were studied. The 28-day mortality of intracerebral hemorrhage was 44.44% and it was 29.30% within the first 7 days of onset. Maximum number of death occurred in brainstem haemorrhage (75%), initial haematoma volume 61 to 80 ml (89.47%), >80 ml (91.7%), pineal gland displacement >3mm (79.5%), septum pellucidum displacement >5 mm (72.4%), ventricular extension (88.57%), and hydrocephalus (76.74%).
 Conclusion: The present study shows that deaths within 7th and 28th day of acute haemorrhagic stroke are correlated with the initial CT findings which could be regarded as a good predictor of mortality.
 Journal of National Institute of Neurosciences Bangladesh, 2019;5(1): 42-46