Clinical and biochemical predictors of late-outcome in patients after ischemic stroke

Abstract

Objective. The aim of this study is to evaluate neurological scales, as well as biochemical and radiological parameters measured on day 10 after ischemic stroke (IS), according to their value as predictors of the long-term outcome. Materials and method. 45 patients were assessed according to the Barthel Index (BI) and National Institute of Health Stroke Scale (NIHSS) on day 10, and according to Modified Rankin Scale (mRS) 3 months after the onset of IS. On day 10 of IS, the serum level of C-reactive protein (CRP), albumin, D-dimers (DD), S100BB and Tau proteins was measured and the volume of ischemic focus assessed with the use of Computed Tomography (CT). The patients were divided into groups with good outcome (GO) and mRS 0-2, and with bad outcome (BO) and mRS 3-6. Results. NIHSS and BI scores (p<0.001), the volume of ischemic focus (p<0.01), CRP (p<0.01) and albumin level (p<0.05), but not DD, S100BB and Tau protein levels evaluated on day 10, correlated with mRS after 3 months since IS onset. Patients from the BO group were observed to have lower BI (p=0.001), higher NIHSS (p<0.01) and CRP levels (p<0.05), and bigger volume of ischemic focus (p<0.05) measured on day 10 of IS. In the GO group, there were more patients with atherosclerotic etiology (p=0.02 x2=7.856). Regression analysis showed that only the BI score assessed on day 10 of IS can predict the outcome after 3 months assessed by mRS (OR=1.102, 95%, CI:1.01-1.203; p=0.001). Conclusions. BI assessed on day 10 has a predictive value for the outcome evaluated by mRS 3 months after the onset of IS.

Optimizing acute stroke outcome prediction models: Comparison of generalized regression neural networks and logistic regressions

“…Aged stroke patients may have higher mortality, longer hospital stay, and poorer quality of life than their younger counterparts [ 35 ]. Bielewicz et al [ 6 ] reported that the BI scores assessment on day 10 was predictive of outcomes 3 months after ischemic stroke onset, indicating that the preexisting functional status was positively correlated with the prognosis of stroke patients. Besides, the NIHSS score has been shown to reflect neurological deficits and is considered valuable for predicting the outcome of stroke patients [ 6 ].…”

“…The variables were screened based on previously published articles and clinical experience [ 6 , 11 , 20 ]. Accordingly, 25 clinical variables were used in this study, and the data of the 216 patients were randomly divided into training (n = 168, 80%) and test (n = 48, 20%) sets using the Kennard-Stone algorithm.…”

“…The LR model is used for classification based on certain predictors [ 12 ]. The dependent variable of LR is usually a binary variable, such as the outcomes (good or bad) of acute stroke patients [ 6 ]. For this model, the probability of a stroke outcome, given as, in relation to n prognosis-related covariates, X 1 , X 2 , X 3 , ⋯ , is given as follows: …”

“…To mitigate pressure on the healthcare system, assist medical professionals in making optimal clinical decisions [ 3 ], assist therapists in setting realistic therapeutic goals, improve the quality of life and life expectancy of acute stroke patients [ 4 ], as well as inform educated decisions on posthospital service needs for patients [ 5 ], accurate prognostic prediction is imperative. Besides, accurate outcome predictions would also assist policymakers and care providers in setting appropriate healthcare goals and optimizing the allocation of medical resources [ 6 ].…”

“…Some are too complex for use in the clinical context, and others are susceptible to bias [ 10 ]. Consequently, establishing a reliable and feasible model for stroke prognosis prediction is an important challenge for rehabilitation physicians [ 6 ].…”