The Relative Impact of Clinical and Investigational Factors to Predict the Outcome in Stroke Patients.

Objective: As stroke is still considered a significant cause of mortality and morbidity, it is crucial to find the factors affecting the outcome in these patients. We aimed to interpret the various clinical and investigational parameters and establish their association with the outcome in stroke patients.

Materials and methods: This is a retrospective, cross-sectional study, conducted in the Department of Neurology between June 2019 to November 2021. The study involved the review and analysis of medical records pertaining to 264 patients, admitted with the diagnosis of stroke. Various clinical, radiological, and electroencephalographic (EEG) patterns in stroke patients were analyzed and their association with outcome was established. The association between the studied variables was performed by the logistic regression (LR) and presented as odds ratio (OR) and 95% confidence interval (CI).

Results: The study sample consisted of 264 patients. Males comprised 165 (62.5%) with the mean participant age of 57.17 ± 18.7 3 years (range: 18-94). Patients younger than 50 years had a better likelihood of a good outcome in comparison to patients older than 50. The admission location was the most significant factor in predicting the outcome ( P = 0.00) in favor of inpatient department and outpatient department (OPD), in contrast to patients admitted directly to intensive care unit (ICU). Normal EEG was associated with good outcome ( P = 0.04; OR, 3.3; CI, 1.01-10.88) even after adjustment of the confounders, whereas patients having marked EEG slowing had a poor outcome ( P = 0.05; OR, 2.4; CI, 0.65-8.79). Among the clinical parameters, hemiparesis ( P = 0.03), trauma ( P = 0.01), generalized tonic-clonic seizures (GTC) ( P = 0.00), and National Institutes of Health Stroke Scale of more than 4 were more likely associated with a poor outcome as well as the presence of intracranial hemorrhage (ICH) or infarction in the cortical and cortical/subcortical locations were associated with poor outcomes. After adjustment of confounders, the factors found to have prognostic significance in favor of good outcomes were inpatients or OPD referrals and normal EEG while direct admission to ICU, marked slowing on EEG, and presence of ICH were found to be associated with poor outcome.

Conclusion: Certain patterns are predictive of good or worse outcomes in stroke patients. Early identification of these factors can lead to early intervention, which in turn might help in a better outcome. The results of the study, therefore, have some prognostic significance.