Integrated multidisciplinary assessment of cerebral stroke outcome after treatment in a comprehensive stroke unit
Objective – to explore the possibility of integral assessment of the stroke outcome and to develop a method of integral assessment of the stroke outcome after in-patient treatment on the level of impairment and and the level of activities of daily living, which were assessed using rating scales and indices.
Materials and methods. The study was conducted at the Stroke Center (SC), Oberig’ multidisciplinary hospital division, which operates according to the principles of Comprehensive Stroke Unit. Patients with a cerebral stroke who were admitted to the SC in 2010–2018 were enrolled. The data of the participants were prospectively entered into a special database and included discharge assessments using 8 valid rating scales and indices. Cluster analysis methods (in particular Kohonen neural networks) were used to design the integral assessment. Statistical analysis of the values of the rating scales and indices in the selected clusters was performed using the Kruskal–Wallis criterion, post hoc comparisons were made using the Dunn multiple comparison criterion.
Results. 852 patients (42.5 % women and 57.5 % men, median age – 66.7 year) were enrolled. 81 % of patients were diagnosed with ischemic stroke, and 19 % had hemorrhagic stroke. According to the chosen method, it is necessary and sufficient to split the data into 4 clusters. All participants in the study according to their assessments at discharge using the set of selected measures could be assigned to one of 4 isolated clusters: K1 (n = 366), K2 (n = 93), K3 (n = 104) or K4 (n = 289). National Institutes of Health Stroke Scale, modified Rankin scale, Barthel Index, Berg Balance Scale та Functional Ambulation Classification were the most significant determinants of the patient cluster. For the 5 measures there have been significant differences (p < 0.001) in the four clusters. The condition of the patients in K4 cluster was the best (p < 0.05), whereas the patients in the K1 cluster were worse (p < 0.05), and the condition of the patients in the clusters K2 and K3 was much worse (p < 0.05) compared with the cluster K4.
Conclusions. Based on the integrated assessments of neurological impairments and activities of daily living all of stroke patients could be assigned to one of four identified clusters. Detecting predictors of poor outcome after in-patient management may help to find ways to improve their prognosis.
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