Modeling the outcomes of thrombolytic therapy in ischemic stroke

Abstract

Aim to predict the effectiveness of systemic thrombolysis based on a comprehensive assessment of risk factors at the stage of decision making for thrombolytic therapy.
 Material and methods. The study included 110 ischemic stroke patients hospitalized between 2016 and 2021 who received the rt-PA systemic thrombolytic therapy. Depending on the outcome of the disease, all patients were ranked into two groups. Group I (favorable outcome) included 79 patients who had regression of focal neurological deficit, assessed using the NIHSS, mRS, Rivermead scales. Group II (unfavorable outcome) included 31 patient, among whom 4 patients had a worsening condition, expressed as an increase in focal neurological deficit, assessed using the NIHSS scale, as well as 27 patients who developed a lethal outcome.
 Results. The following factors were revealed having the greatest impact on the outcome of the thrombolytic therapy: the age of patients, the time passed from the development of stroke symptoms to systemic thrombolysis, the severity of neurological deficit, the ASPECTS score at admission, the blood glucose level at admission. In order to group the array of processed clinical, laboratory and neuroimaging data, we used a two-stage cluster analysis. Four clusters were formed in the process of cluster analysis. A mathematical model was developed in order to improve the efficiency of systemic thrombolysis and to predict the outcome of the disease in patients with ischemic stroke, which was tested on the basis of the neurological department of the Regional Clinical Hospital named after V.D. Seredavin.
 Conclusion. The application of this mathematical model based on medical information systems will make it possible to stratify the risk of disease outcome in patients with ischemic stroke timely and effectively at the stage of the emergency department in the vascular centers and primary vascular departments of the city of Samara.