A b s t r a c tBackground: Studies published during the last decade seem to indicate red blood cell parameters as inexpensive, rapidly available, and simple tools for the assessment of prognosis in patients with chronic heart failure (CHF). Aim:To evaluate the prognostic value of red cell parameters determined in a routine blood count in patients with CHF. Methods:The study group included 165 patients with the New York Heart Association (NYHA) class II-IV CHF hospitalised in the 2 nd Department of Cardiology in Bydgoszcz. On the first day of hospitalisation, all patients in the study group underwent a complete blood count with an assessment of haemoglobin (Hb) level, mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC) and red blood cell distribution width (RDW). Follow-up was carried over 24 months by phone calls every 3 months.Results: MCV, MCH and MCHC were not shown to be significant predictors of mortality in CHF patients at 1 and 2 years of follow-up. In univariate analysis at 1-year follow-up, the following variables were significantly associated with the occurrence of the study endpoint: Hb level (p = 0.022; HR = 0.80), RDW (p = 0.004; HR = 1.257), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) level (p = 0.0001; HR = 1). At 2 years of follow-up, the following variables were significantly associated with the occurrence of the study endpoint: left ventricular ejection fraction (p = 0.018; HR = 0.956), NYHA class (p = 0.007; HR = 0.378), RDW (p = 0.044; HR = 1.175), and NT-proBNP level (p < 0.001; HR = 1). Multivariate analysis for 1-year follow-up showed that RDW and NT-proBNP level were independent significant predictors of mortality, while NT-proBNP level (p = 0.006; HR = 1) and NYHA class (p = 0.024; HR = 0.439) were significant predictors of mortality at 2 years of follow-up. Based on receiver operating characteristic curve analysis, the cut-off RDW was 15.00% (AUC = 0.63; 0.523-0.737), at 12 months of follow-up and 14.00% (AUC = 0.6; 0.504-0.697), at 24 months of follow-up. The cut-off for Hb level was 13.9 g/dL (AUC = 0.662; 0.553-0.77), at 12 months of follow-up and 12.2 g/dL (AUC = 0.581; 0.482-0.681), at 24 months of follow-up. Conclusions:Baseline RDW and Hb level in patients hospitalised with the diagnosis of NYHA class II-IV CHF seem to be important predictors of mortality in this population. Among the red blood cell parameters, only RDW was shown to be an independent prognostic factor at 1 year of follow-up but it appeared to lose its significance during longer-term follow-up.
The VaR method allows for risk measurements and estimations of the highest expected loss on a portfolio at an assumed confidence level over a specified time horizon. The most important assumption affecting the calculation method is that price changes in financial markets follow a normal distribution. Findings: It appears that by appropriately re-defining the concepts of assets and portfolio rates of return, we can describe the volatility in the numbers of deaths caused by Covid-19. We also confirmed using the Shapiro-Wilk and Skewness and Kurtosis tests that the rates of return distribution for the death numbers follow a normal distribution. Practical Implications: The VaR method allows to estimate the number of deaths based on current trends which can be utilised to better manage available resources in order to reduce casualties. We use the data regarding the number of deaths in the Visegrad Group (V4) countries as a case study to test the effectiveness and accuracy of the VaR method in a different, non-financial domain. Originality/Value: The theory we used in this paper is currently mainly applied to financial investments. We use this theory to describe social phenomenon which is the number of deaths, our approach has not been seen in the literature so far.
Selected econometric methods of modelling the world's population size based on historical data are presented in the paper. Periodical variables were used in the models proposed in the paper. Moreover, a logistic-type function was used in modelling. The purpose of the paper was to obtain a model describing the world's population with the lowest possible maximal relative error and possibly the longest period of durability. In this work, 13,244 models from three families models were analyzed. Only a small part of such a large number of models satisfies the conditions of stability. The method of modelling the world's population size allows to obtain models with maximal relative errors not exceeding 0.5%. Selected models were used to prediction of the world's population up to 2050. The obtained results were compared with data published by the Organisation for Economic Co-operation and Development.
The relevance of the analysis of Sustainable Development Goals is based on the 2030 Agenda for Sustainable Development. The purpose of the study is to create a model of management/regulation of the quality of education and scientific research systems based on Sustainable Development Goals. The data of the ratings that reflect certain tasks of the Sustainable Development Goals, including those related to educational and scientific activities, are analyzed. The methodology of calculating the index of the success of realization of separate purposes of sustainable development is used. Bibliometric analysis as a research tool is used to create a quality of education management model. The example of the roadmap for achieving SDGs within the relationship chain “quality of education and science + partnership and networks–innovation–socio-economic impact–sustainable development goals” is provided. The suggested methodology for determining the index of success in achieving Sustainable Development Goals includes managing education systems, implementing scientific research, and managing/regulating the economy on micro-(university), meso-(regional), and macro-(national) levels. The tool in this case is a strategy for achieving KPIs, which can be fundamentally implemented in the form of a roadmap, with detailing of its elements using other tools. The “management/regulation” stage of the process of achieving Sustainable Development Goals is concretized by a mind map.
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