Prediction of the Lethal Outcome of Acute Recurrent Cerebral Ischemic Hemispheric Stroke
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Prediction of the Lethal Outcome of Acute Recurrent Cerebral Ischemic Hemispheric Stroke / O. A. Kozyolkin, A. Kuznietsov, L. V. Novikova // Medicina. - 2019. - Vol. 55, № 6. - P. 311. - https://doi: 10.3390/medicina55060311.
Abstract
Background and objectives. Stroke-induced mortality is the third most common cause of
death in developed countries. Intense interest has focused on the recurrent ischemic stroke, which
rate makes up 30% during first 5 years after first-ever stroke. This work aims to develop criteria
for the prediction of acute recurrent cerebral ischemic hemispheric stroke (RCIHS) outcome on the
basis of comprehensive baseline clinical, laboratory, and neuroimaging examinations. Materials and
Methods. One hundred thirty-six patients (71 males and 65 females, median age 74 (65; 78)) with
acute RCIHS were enrolled in the study. All patients underwent a detailed clinical and neurological
examination using National Institutes of Health Stroke Scale (NIHSS), computed tomography of
the brain, hematological, and biochemical investigations. In order to detect the dependent and
independent risk factors of the lethal outcome of the acute period of RCIHS, univariable and
multivariable regression analysis were conducted. A receiver operating characteristic (ROC) analysis
with the calculation of sensitivity and specificity was performed to determine the prediction variables.
Results. Twenty-five patients died. The independent predictors of the lethal outcome of acute RCIHS
were: Baseline NIHSS score (OR 95% CI1.33 (1.08–1.64), p = 0.0003), septum pellucidum displacement
(OR 95% CI 1.53 (1.17–2.00), p = 0.0021), glucose serum level (OR 95% CI 1.28 (1.09–1.50), p = 0.0022),
neutrophil-to-lymphocyte ratio (OR 95% CI 1.11 (1.00–1.21), p = 0.0303). The mathematical model,
which included these variables was developed and it could determine the prognosis of lethal outcome
of the acute RCIHS with an accuracy of 86.8% (AUC = 0.88 ± 0.04 (0.88–0.93), p < 0.0001).