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The mortality rate after ischemic stoke is influenced by various factors. Prognosis after ischemic stroke can be predicted using a scoring system to help the doctor to evaluate patient’s condition, neurologic deficits, and possible prognosis as well as make appropriate management decisions. The objective of this study was to identify the factors which determine mortality rates in patients after ischemic stroke and to determine the prognosis of ischemic stroke patients using the predictive mortality score.
This was a nested case control study using data from the stroke registry and medical records of patients at the Neurology Clinic of Bethesda Hospital Yogyakarta between 2011-2015. Data was analysed using simple and multiple logistic regression analysis. The scoring was analyzed using receiver-operating characteristic (ROC) curve and the cut-off point using area under the curve (AUC).
Multiple logistic regression analysis showed a significant association between mortality of ischemic stroke patients and age (OR: 4.539, 95% CI: 1.974-10.439, p<0.001), random blood glucose (OR: 2.692, 95% CI: 1.580-4.588, p<0.001), non-dyslipidemia (OR: 2.313, 95% CI: 1.395-3.833, p=0.001), complications (OR: 1.609, 95% CI: 1.019-2.540, p=0.041), risk of metabolic encephalopathy (OR: 2.499, 95% CI: 1.244-5.021, p=0.010) and use of ventilators (OR: 17.278, 95% CI: 2.015-148.195, p=0.009).
Age, high random blood glucose level, complications, metabolic encephalopathy risk and the use of ventilators are associated with mortality after ischemic stroke. The predictive mortality score can be used to assess the prognosis of patients with ischemic stroke.
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