Shahin Rouhani
Tabriz University of Medical Sciences, Iran
Scientific Tracks Abstracts: J Neurol Neurophysiol
Introduction: Cerebrovascular accident (CVA) has been the third leading cause of death and disability, in developed countries. Individuals suspected of having stroke should be taken immediately to a medical facility for diagnosis and treatment. The symptoms following a stroke are not significant however these manifestations depend on the area of the brain that has been affected and its function. Parameters for predicting long-term outcome in such patients have not been delineated clearly. Therefore, the aim of this study was to investigate this possibility and to test a system that might practically be used routinely to aid management and predict outcomes of individual stroke patients. Methods & Materials: A cross-sectional hospital-based study of the symptoms and signs including severe headache, seizure, vomiting, eye movement disorder, pupil size, pupil reflex to light, GCS, confusion, blood pressure, heart rate, respiratory rate, and body temperature of 503 patients with ischemic stroke was performed. Results: In a Logistic model, we could predict the type of CVA by using respiratory rate, severe headache, vomiting, and dilated pupils with high accuracy (accuracy: 97.4%). Elevation in respiratory rate, can lead to 1.258 fold raise in hemorrhagic than ischemic stroke. While it is about 110.224 fold with headache, 4.59 fold with vomiting and 6.645 fold with dilated pupils. Conclusion: Although this model provides a well-tested tool for stratification in Trials, imaging modalities are the discriminating instruments for diagnosis because of the improvement in these methods. Validity of this model should be evaluated in future studies.
Shahin Rouhani is currently pursuing her Post-doctoral studies in Medicine faculty and Students research committee, Tabriz University of Medical Sciences, Tabriz, Iran. He has published more than 4 papers in reputed journals.
Email: shahin_roohani@yahoo.com
