Aim of the study. The 4C Mortality Score was created to predict mortality in hospitalised patients with COVID-19 and has to date been evaluated only in respiratory system disorders. The aim of this study was to investigate its application in patients with COVID-19-associated acute ischaemic stroke (AIS).Clinical rationale for study. COVID-19 is a risk factor for AIS. COVID-19-associated AIS results in higher mortality and worse functional outcome. Predictors of functional outcome in COVID-19-associated AIS are required. Materials and methods.This was a retrospective observational study of patients with AIS hospitalised in seven neurological wards in Małopolska Voivodship (Poland) between August and December 2020. We gathered data concerning the patients' age, sex, presence of cardiovascular risk factors, type of treatment received, and the presence of stroke-associated infections (including pneumonia, urinary tract infection and infection of unknown source). We calculated 4C Mortality Score at stroke onset, and investigated whether there was a correlation with neurological deficit measured using the National Health Institute Stroke Scale (NIHSS) and functional outcome assessed using the modified Rankin Scale (mRS) at discharge. Results.The study included 52 patients with COVID-19-associated AIS. The 4C Mortality Score at stroke onset correlated with mRS (r s = 0.565, p < 0.01) at discharge. There was also a statistically significant difference in the mean 4C Mortality Score between patients who died and patients who survived the stroke (13.08 ± 2.71 vs. 9.85 ± 3.47, p = 0.04).Conclusions and clinical implications. 4C Mortality Score predicts functional outcome at discharge in COVID-19-associated AIS patients.
The purpose of the article is to build a gravitational growth model of Ukrainian economy. The correlation of the labour productivity macroeconomic indicator and its empirical verification is considered. The article looks at recent research dealing with data analysis of region groups as of 2004-2017. To determine the conditions for economic development of the regions, the magnitude and the possible influence of the main macroeconomic factors were assessed. The methodology of gravity modelling makes it possible to study the significance of each individual factor on the basis of statistical information and to predict these factors within the context of possible scenarios. Methods of statistical analysis and econometric modelling were used to build a gravity model and to assess its statistical significance and forecasting ability for economy. The methodological principles of the gravity theory in the context of the set tasks involve studying both regional GDP indicators and the geographical location and remoteness from the capital. The paper presents the influence of two macroeconomic aggregates on the dynamics of economic development -labour productivity and physical capital per worker, with account of their relationship to gravitational effects. The economic analysis uses regional statistical data available on the website of the State Statistical Service of Ukraine. As a result, three main conclusions were formulated. First, 2001-2008 was the most favourable period for the development of Ukrainian economy (after the restoration of Ukraine's independence in 1991). Second, future strong positions of the Northern Ukraine were identified (Kyiv city, Kyiv region with account taken of the expected side effect). Third, a long-term one, to implement the regional development policy the volume of regional investment should be increased. In turn, investment attractiveness of the remote regions, with a relatively low expected economic polarization, will also increase.
: The aim of the present study is to design a bipolar model of economic growth with investment flows between two types of economies (conventionally referred to as relatively rich economies and relatively poor economies). Therefore in the following considerations it is assumed that the process of capital accumulation depends on investments undertaken in the economy. At the same time the Solow growth model takes into account only investments financed by domestic savings, whereas in the bipolar growth model also the investment flows between rich and poor economies are considered. It is assumed that both relatively rich economies are investing in the relatively poor economies and the poor economies make investments in the rich economies.The paper analyses the long-term equilibrium of the growth model, both in terms of existence of steady states of the system of differential equations and in terms of the stability of a non-trivial steady state. What is more economic characteristics of the point of the long-term equilibrium of the model are examined, model parameters are calibrated and growth paths of basic macroeconomic variables in selected variants of numerical simulations are presented.
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