OBJECTIVE

To study predictors of unfavorable outcomes in ischemic stroke associated with COVID-19.

MATERIAL AND METHODS

A retrospective analysis of 173 case histories of patients with ischemic stroke and COVID-19 was carried out. The average age was 68.64±11.39 (95% CI 66.93—70.35; median 92, mean 34) years. By gender, women predominated (64.16%). Fatal outcome was observed in 62 (35.84%) patients. Risk factors were studied using binary logistic regression.

RESULTS

The risk of a fatal stroke in a univariate analysis was established in the presence of a general severe condition of the patient and a number of other factors, which included the severity of COVID-19, acute coronary syndrome, multiple organ failure, the need for a ventilator, a history of kidney disease, pneumonia, high NIHSS score, oxygen partial pressure level, respiratory rate, number of hospitalizations, complete blood count (erythrocytes, hemoglobin, hematocrit, leukocytes, neutrophils), coagulogram, glucose, liver and kidney markers (bilirubin, aspartate aminotransferase, alanine aminotransferase, creatinine, urea), levels of creatine phosphokinase, lactate dehydrogenase and C-reactive protein. A model based on multivariate analysis was used, which makes it possible to predict the probability of a fatal outcome. A regression function was obtained, which included the content of C-reactive protein, urea and NIHSS score. In patients with a value of 35% and above, there was an increased risk of death, in the case of a value below 35%, a favorable outcome was assumed. The model was statistically significant (p<0.001). The sensitivity and specificity of the model were 88.9% and 97.9%, respectively.

CONCLUSION

The revealed predictors of the probability of a fatal stroke outcome can be guidelines for a Coctor in choosing a patient management strategy at different stages of patient care.