Combination of five clinical data as prognostic factors of mortality after ischemic stroke
Abstract: 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.
Methods
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).
Results
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).
Conclusions
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.
Keywords: Ischemic stroke;
causes of mortality; predictive mortality score
Author: Rizaldy Taslim Pinzon,
Fransiska Theresia Meivy Babang, Esdras Ardi Pramudita
Journal Code: jpkedokterangg170026
